JP5748900B2 - Provision of real-time segment performance information - Google Patents

Description

CROSS-REFERENCE Other applications are incorporated herein by reference for all purposes, the entitled as "MOBILE GLOBAL POSITIONING SYSTEM (GPS) DEVICE FOR PROVIDING REAL-TIME FEEDBACK ", March 2011 Claims priority based on US Provisional Patent Application No. 61 / 470,238, filed 31 January.

  Traditionally, GPS devices have been able to record and store the athlete's GPS position and other data points (eg altitude, heart rate) during the athlete's physical activity (eg running, cycling), and The GPS device may be able to upload these data points incrementally to a remote server while performing such physical activity.

  Various embodiments of the invention are disclosed in the following detailed description and the accompanying drawings.

FIG. 3 illustrates a system for defining and matching segments according to some embodiments.

FIG. 3 illustrates one embodiment of a segment matching server, according to some embodiments.

FIG. 4 illustrates an example of effort stored in a table of an effort database, according to some embodiments.

6 is a flowchart illustrating one embodiment of a process for segment matching in accordance with some embodiments.

7 is a flowchart illustrating one embodiment of a process for defining a segment based on effort, according to some embodiments.

FIG. 4 illustrates an example user interface for defining segments based on effort, according to some embodiments.

FIG. 4 is a diagram illustrating an example of a user interface illustrating the selection of a segment start point according to some embodiments.

FIG. 4 is a diagram illustrating an example of a user interface illustrating the selection of a goal point for a segment according to some embodiments.

FIG. 4 illustrates an example user interface for defining a segment using a series of selections on a map, according to some embodiments.

6 is a flowchart illustrating one embodiment of converting a series of GPS information into a minimum circumscribed rectangle (MBR), according to some embodiments.

FIG. 4 illustrates an example of converting a series of GPS information into a set of MBRs according to some embodiments.

FIG. 6 is a diagram illustrating an example of a database table entry for storing segment information according to some embodiments.

6 is a flowchart illustrating one embodiment of a process for searching for a matching segment in a segment database, according to some embodiments.

6 is a flowchart illustrating one embodiment of matching effort to a segment in accordance with some embodiments.

FIG. 3 illustrates an example of creating a virtual start line according to some embodiments.

6 is a flowchart illustrating one embodiment of a process for determining a matching effort according to some embodiments.

FIG. 6 illustrates an example display of data analyzed for matched effort, according to some embodiments.

FIG. 4 illustrates one embodiment of a system for providing real-time feedback during current activity associated with a segment, according to some embodiments.

FIG. 3 illustrates a user utilizing a system 1500 while performing an activity, according to some embodiments.

FIG. 3 illustrates one embodiment of a segment matching server, according to some embodiments.

6 is a flowchart illustrating one embodiment of a process for providing real-time feedback during current activity associated with a segment, according to some embodiments.

6 is a flowchart illustrating one embodiment of a process for setting parameters related to sending information recorded at a device to a remote segment matching server, according to some embodiments.

6 is a flowchart illustrating one embodiment of a process for prefetching segment data from a server and generating real-time feedback at a device according to some embodiments.

6 is a flowchart illustrating one embodiment of a process for setting parameters relating to a filter on data acquired for comparison with performance data of a user's current activity.

6 is a flowchart illustrating one embodiment of a process for matching a segment to a user's current activity in accordance with some embodiments.

6 is a flowchart illustrating one embodiment of a process for determining a user's progress along a segment according to some embodiments.

6 is a flowchart illustrating one embodiment of a process for communicating real-time performance information regarding a user's current activity in accordance with some embodiments.

FIG. 4 is a screenshot of a user interface displaying a leaderboard for effort completed in a “Marincello Trail” segment, according to some embodiments.

FIG. 6 is a screenshot of a user interface displaying a list of detected segments (“climbs”) located near a user's current activity, according to some embodiments.

FIG. 6 is a screenshot of a user interface displaying a map of detected segments (“climbs”) located near a user's current activity in accordance with some embodiments.

  The present invention is a process, apparatus, system, composition of matter, computer program product embodied on a computer readable storage medium, and / or processor (stored in and / or stored in a memory connected to a processor). A processor configured to execute the provided instructions) and can be implemented in various forms. In this specification, these implementations or any other form that the invention may take may be referred to as techniques. In general, the order of the steps of disclosed processes may be altered within the scope of the invention. Unless stated otherwise, a component such as a processor or memory that is described as being configured to perform a task is a general component that is temporarily configured to perform a task at a certain time, or It may be implemented as a particular component that is manufactured to perform a task. As used herein, the term “processor” is intended to refer to a processing core configured to process one or more devices, circuits, and / or data such as computer program instructions.

  The following provides a detailed description of one or more embodiments of the invention with reference to the drawings illustrating the principles of the invention. Although the invention has been described in connection with such embodiments, it is not limited to any embodiment. The scope of the invention is limited only by the claims and includes many alternatives, modifications, and equivalents. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. These details are for the purpose of illustration, and the present invention may be practiced according to the claims without some or all of these specific details. For the purpose of simplicity, technical material that is known in the technical fields related to the invention has not been described in detail so that the invention is not unnecessarily obscured.

  Disclosed herein is defining a segment and matching the effort to the segment. As used herein, a segment is a geographic path of interest as a reference (eg, a comparison of exercise performance along the path and / or other uses). Available. For example, the segments can be used to identify hill climb courses that are popular with cyclists. As used herein, an effort is a series of recorded GPS information with a time stamp (eg, may represent athletic performance). In some embodiments, the effort is stored with associated data (eg, a measure of activity with which the effort is associated). In some embodiments, one or more segments are derived from the stored effort. In some embodiments, the user can define segments. In some embodiments, a visual representation of the effort is presented on the user interface, and the user defines the segment using the visual representation. In some embodiments, a map is presented on the user interface and the user defines the segment by showing a route on the map. In various embodiments, a series of GPS information is converted into a set of geographic abstractions before being stored as segments. In some embodiments, the segment is stored with the associated data of the effort determined to match the segment.

  In various embodiments, the effort is matched with the stored segment. In various embodiments, two levels of matching can be performed using effort and stored segments. In a first level of matching, a first decision is made when the effort match rate for one of the stored segments exceeds a first threshold (eg, an effort is a loose match for a segment). ). In the second level of matching, the effort match rate for one of the stored segments exceeds a second threshold (greater than the first threshold), and the effort crosses the segment start and goal lines. A second decision is made (e.g., if the segment crosses the start line and goal line of the segment) (or if it is determined that the segment forms a loop and the loop segment entry point is exceeded a second time) (e.g., Effort is an exact match for a segment). In some embodiments, the effort can be determined to be a loose match for one or more stored segments, and the effort can be further determined to be an exact match for one or more stored segments. In some embodiments, if the effort matches a segment (eg, as either a loose match or an exact match), the effort related data is compared to the related data stored with the matched segment. In some embodiments, if the effort matches a segment, the effort related data is also compared with other effort related data matching the segment.

  FIG. 1 is a system for defining and matching segments according to some embodiments. The system 100 includes a device 102, a network 104, and a segment matching server 106. Network 104 includes various high-speed data networks and / or telecommunications networks. Device 102 communicates with segment matching server 106 through network 104. In some embodiments, the system 100 may include a different number of components than shown in the example of FIG.

  Device 102 is a device that can record GPS information and / or other data related to physical activity. The device 102 may further be a device to which GPS information and / or other data related to physical activity may be uploaded or transferred. Examples of device 102 include a GPS device (eg, Garmin Forrunner 110, 205, 301, 305, 310XT, 405, 405CX, and Garmin Edge 305, 605, 705, 500, Garmin Forrunner and Edge devices), GPS recording Mobile phones, computers, tablet devices, and / or other general purpose computer devices and / or special purpose computers such as smartphones (eg, Android devices or Apple iPhone devices) with applications (eg, MotionX, Endonmondo, and RunKeeper) Devices, but not limited to, these are generally generic Comprising a processor, a memory, or other storage element, the network or input and output (I / O) capabilities and, the, the interface for the integrated GPS function or support or GPS device or GPS function.

  In various embodiments, the device 102 (or its application) is configured to record GPS information and data related to physical activity during activity. In some embodiments, the device 102 is configured to receive recorded GPS information and data related to the active physical activity after the activity ends (eg, such information uploaded to the device 102). ) In some embodiments, the recorded GPS information and associated data is referred to as “effort”. In other words, effort is an event of physical activity and can be represented by geographic information and other measurements related to exercise performance. Examples of physical activity include cycling, running, and skiing. In some embodiments, the GPS information includes a series of continuous and discrete GPS data points (eg, latitude and longitude), with a time stamp for each point. In some embodiments, the relevant data includes elevation, heart rate, power / wattage (eg, energy consumed), time, speed (eg, average and / or maximum speed per segment and / or route, For example, the average speed may be derived from time and GPS information), but is not limited thereto. Related data can be recorded at various granularities. For example, the relevant data may correspond to each GPS data point, the entire activity (eg, the relevant data includes an average of measurements), or a portion of the activity. As an example, the device 102 can be utilized during cycling. At the end of cycling, the user will be able to follow the geographical path that the user has followed, how much energy the user has consumed in cycling, how quickly he has scored, average speed, measurements based on elevation, and / or other You can look back on your performance along with recorded GPS information (eg, through the user interface of device 102) to see your measurements. In some embodiments, the device 102 is configured to store recorded GPS information and associated data (eg, effort) and / or send effort information to the server 106. In some embodiments, the device 102 is configured to present an interactive user interface. The user interface may display GPS information and receive selections regarding those displays (eg, made by the user). In some embodiments, the device 102 sends the received selection to the segment matching server 106.

  In various embodiments, the segment matching server 106 is configured to support and present the user interface of the device 102. In some embodiments, the segment matching server 106 is configured to receive user-defined segments at the user interface using the recorded effort. A segment means a geographic path of interest and can be used as a reference for comparison of athletic performance along the geographic path. The segment matching server 106 is configured to receive a series of GPS information and related data (eg, effort). In some embodiments, the segment matching server 106 is configured to display a visual representation of GPS information on a user interface using a map software application. The visual representation may be, for example, a series of flags or continuous lines marked on the map. In some embodiments, the segment matching server 106 interacts with an application programming interface (API) of a map software / application (eg, Google Map, MapQuest, Bing map, and / or another mapping application / service). By providing logic configured to work, the user interface can support maps. In some embodiments, the user can define segments using a visual representation of GPS information. In some embodiments, along with a visual representation of GPS information, start points and goal points (eg, end points) are selected on the map to define the segment. For example, the user can select start points and / or goal points (eg, by dropping or clicking a marker) along a geographic path followed during physical activity. In this way, the part of the geographical path between the selected start point and goal point is defined as a segment. In some embodiments, start points and goal points are stored with defined segments. In some embodiments, a portion of the geographic path between the start point and the goal point is stored in a database for storing segments after being converted to an abstract form. In some embodiments, relevant data corresponding to the defined segment is also stored in the database along with the segment.

  In some embodiments, the segment matching server 106 is configured to receive user-defined segments at the user interface using map choices. In some embodiments, the segment matching server 106 presents a map (eg, Google Map, MapQuest) and receives a series of point selections on the map to indicate the course of the segment. The sequence of point selections on the map need not be based on the recorded effort, but can simply be any geographic path of interest. For example, the selected segment may be a path that the cyclist has previously run but not recorded, and the selected segment may be the path that the cyclist wants to run in the future. A series of point selections on the map can be converted into a series of GPS information (eg, coordinates). In some embodiments, the series of GPS information is stored as segments after being converted to an abstract form.

  In some embodiments, after a segment is defined in the user interface, a stored effort (eg, a set of GPS information from past physical activity) is compared to the defined segment. In some embodiments, when the effort is compared to this defined segment, in part, by checking whether the effort's GPS information indicates that it has passed the start and goal points, It is determined whether the effort matches the segment. If it is determined that one or more efforts match the segment, the data associated with the effort is retrieved and analyzed. In some embodiments, data associated with the newly defined segment is also included in the analysis. For example, by comparing the data, it can be determined which effort that matches the segment has the fastest time to complete the segment.

  The segment matching server 106 is further configured to match an effort (eg, a set of GPS information) to the segment. In some embodiments, the effort is converted to the same abstract form as the stored segment before determining the effort match. One purpose of matching effort to a segment is to find stored physical activity cases (ie, segments) that have taken place over the same delimited path of interest. In other words, an effort that matches a segment is an instance of physical activity performed along a defined track. When multiple instances of physical activity that occur in the same segment are found, their associated information (eg, end time, speed, heart rate, and / or wattage) is determined by one or more individuals on the same route. Can be compared to produce specific statistics (eg, fastest time, highest wattage) with respect to exercise performance. In some embodiments, for newly defined segments, the segment matching server 106 is configured to compare the stored effort with the segments. In some embodiments, effort related data is stored with the segments determined to match the effort. In some embodiments, the segment matching server 106 is configured to receive the effort (eg, from the device 102) and compare the effort with the stored segment to find a match. In various embodiments, once it is determined that an effort matches a segment, their associated data is compared (eg, the associated data for all efforts that match the segment are compared).

  FIG. 2A is a diagram illustrating one embodiment of a segment matching server, according to some embodiments. In some embodiments, segment matching server 106 may be implemented using the example of FIG. 2A. In the illustrated example, the segment matching server 106 includes a segment database 202, an effort database 204, a definition engine 206, and a matching engine 208. However, the segment matching server 106 may comprise more or fewer components. In some embodiments, the segment matching server is implemented using commercially available general-purpose computer hardware (eg, a host running a Linux operating system on a commercially available server (such as an HP BladeSystem blade server)). Service provider (such as Amazon EC2 cloud).

  The segment database 202 is configured to store defined segments. In the example, the segment database 202 is illustrated as one database, but the segment matching server may include more than one database for storing defined segments. In some embodiments, the segment database 202 is a segment defined by a user uploading stored effort to indicate start and goal points / end points along the visual representation of the effort in the user interface. including. In some embodiments, the segment database 202 includes segments defined by a user making a series of selections along a map path at a user interface. In some embodiments, the segment database 202 is pre-defined (eg, by an administrator of the segment server 106) based on known characteristics of various routes or trails (eg, information provided by professional organizations). Included segments. In some embodiments, the segments are stored in the segment database 202 in an abstract form (eg, as a set of minimum bounding rectangles). One reason for storing segments in an abstract form is to allow efficient search queries for similar segments or matching effort. In some embodiments, the segment database 202 is organized based on an R-tree index. In some embodiments, the segments are stored in the segment database 202 as a set of GPS data points. In some embodiments, each segment in the segment database 202 is stored with an effort identifier from the effort database 204 determined to match the segment. In some embodiments, each segment in the segment database 202 is stored with associated data of effort determined to match the segment.

  The effort database 204 is configured to store the effort as a set of GPS information and time stamps. In the example, the effort database 204 is illustrated as one database, but the segment matching server may include more than one database for storing effort. In some embodiments, the effort database 204 includes effort recorded and uploaded from a device (eg, device 102). The effort stored in the effort database 204 includes at least GPS information, a time stamp corresponding to the GPS information, and a measurement (eg, related data) related to the exercise performance of the effort. In some embodiments, the timestamp is included in the GPS information (eg, the GPS information includes latitude and longitude coordinates along with the corresponding timestamp). In some embodiments, the effort is stored with the identifier of the athlete who performed the effort (eg, the user of device 102). In some embodiments, each effort in the effort database 204 is stored along with an identifier for the segment in the segment database 202 that was determined to match.

  The definition engine 206 is configured to receive the definition of the segment. The definition engine 206 may be implemented in hardware and / or software. In some embodiments, the definition engine 206 is configured to present a user interface (eg, on a device). In some embodiments, the user interface displays a visual representation of the effort (eg, recorded by the device) on the user interface. In some embodiments, the definition engine 206 is through an API to obtain a map service (e.g., displaying a map, receiving a selected GPS coordinate on a displayed map, and / or other map service). It is configured to interact with third party map applications (eg, Google Map, MapQuest). Selection of start points and goal points is made at the user interface and received by the definition engine 206. Next, the definition engine 206 stores the path delimited by the start point and the goal point in the segment database 202 as a segment. In some embodiments, a route on a map displayed by the user interface (eg, shown as a series of selections) is received at the definition engine 206. Then, the definition engine 206 stores the route marked on the map as a segment in the segment database 202. In some embodiments, the definition engine 206 converts the segment to an abstract geographic form (eg, a set of minimum bounding rectangles) before storing the segment.

  In some embodiments, the definition engine 206 is stored in the newly defined segment and segment database 202 to determine whether any existing segment is similar to the newly defined segment. It is configured to compare with segments. In some embodiments, if it is determined that an existing segment is similar to a newly defined segment, a warning that the existing segment exists may be displayed to the creator of the segment. In some embodiments, the creator of the new segment may choose not to save the new segment because a similar segment has already been defined.

  In some embodiments, the definition engine 206 compares (eg, periodically) the segments stored in the segment database 202 to determine whether groups that include two or more segments are similar. It is configured as follows. In some embodiments, for segments determined to be similar, only one segment can be selected to remain in the database (eg, crowdsourcing using a voting process by a community of users utilizing devices such as device 102). As such, those segments are displayed. Unselected segments can be discarded from the database to free up space by removing or demoting extra segments so that they are not displayed as public segments (but are kept for private use by the posting user) Also good). In some embodiments, the definition engine 206 is configured to determine that similar segments include segments that are completely contained in other segments (ie, subsegments and supersegments). In some embodiments, the relationship between a segment and its super segment or subsegment is recorded in the segment database 202.

  Matching engine 208 is configured to determine an effort that matches one or more segments (eg, in segment database 202). In some embodiments, the matching engine 208 is configured to access the effort stored in the effort database 204. In some embodiments, after a user definition of a segment has been made (eg, based on uploaded effort or map markings), matching engine 208 may access the stored effort to define a new definition. Matches the segment that was created. For example, a user (eg, a cyclist) defines a segment (and optionally publishes and shares the segment for viewing by other users), and then traces past past segments that have been defined. Information about activities (eg, past runs by the cyclist himself or other cyclists) can be received. In some embodiments, matching engine 208 is configured to access segments stored in segment database 204. In some embodiments, in response to a received effort (eg, an effort sent by device 102), matching engine 208 matches the received effort with any segment stored in segment database 202. It is determined whether or not to do. For example, a user (eg, a cyclist) can check whether a recently recorded effort (eg, cycling) includes one or more already defined segments. If it is determined that the effort includes a segment, the segment's associated data (eg, athletic performance data) is accessed and compared to the effort's associated data. In this way, the user can benefit from an already defined segment by being able to automatically check whether the user has followed the segment without having to manually determine where the segment starts or ends.

  In some embodiments, the matching engine 208 may store the effort (eg, a set of GPS coordinates) stored in the segment before performing a match with the stored segment (eg, by querying the segment database). To the same abstract form (eg, a set of minimum bounding rectangles). In some embodiments, two types of decisions are made (eg, effort is a loose match, effort is an exact match) based on performing a match between the effort and the stored segment. sell. Effort may be determined to be a loose match with a stored segment if the match rate exceeds a first threshold (eg, 65% or greater). In some embodiments, an effort that is a loose match with a stored segment may mean that the recorded physical activity has approximately followed the same path as the matched segment. If the match rate exceeds a second threshold (eg, 80%) and the effort crosses the start line and goal line associated with the stored segment, the effort is an exact match with the stored segment It can be determined that In some embodiments, an effort that is an exact match with a stored segment may mean that the recorded physical activity followed the exact same path as the matched segment. In various embodiments, for two decisions (eg, loose match and exact match), the match rate determination is performed in the same manner. In some embodiments, an effort may be determined to be a loose match with one or more segments and an exact match with one or more segments (same or different). For example, the effort may be determined to be a loose match with a segment and an exact match with the same segment. In another example, the effort may be determined to be a loose match with a segment and an exact match with a different segment. In some embodiments, a determination that the effort is a loose match is made to one or more segments stored in the first database, and a determination that the effort is an exact match is a first match. For one or more segments stored in two different databases.

  In some embodiments, if an effort is determined to match a segment (eg, as either a loose match or an exact match), the associated data of the segment (eg, stored data determined to match the segment) Effort related data) is accessed for comparison with the Effort related data. In some embodiments, a plurality of stored efforts are determined to match a newly defined segment, and the associated data for the matched segment is accessed, aggregated, and analyzed. In some embodiments, the matching engine 208 is configured to generate an analysis result based on the retrieved data. In some embodiments, the matching engine 208 sends the analysis results to the device 102 (eg, for display on a user interface).

  For example, a user can define a segment, and all stored effort that matches the segment is aggregated and analyzed to provide a list of users that followed the segment with the fastest time or maximum work rate (ie, a standing table). Can be generated. In another example, the user can generate an effort and the segment matching server can determine whether the effort has followed any defined segment. If it is determined that an effort has followed a defined segment, the data associated with that effort can be compared to the history of all efforts determined to have followed the defined segment. In this way, the user can determine how his athletic performance on a segment is compared to all other efforts that have followed the same geographic path (represented by that segment). Furthermore, the user does not need to know the exact location where the segment begins or ends (eg, when the user is riding a bicycle).

  In some embodiments, the device 102 may comprise a segment database 202, an effort database 204, a definition engine 206, and a matching engine 208, and the device 102 does not need to interact with the segment matching server 106. A) device 102 may provide equivalent functionality to store segments, store effort, define segments, and match effort to segments. In some embodiments, the effort database of device 102 includes only the effort generated by the user of that device.

  FIG. 2B is a diagram illustrating an example of an effort stored in a table of an effort database, according to some embodiments. In some embodiments, the effort stored in the effort database 204 may be stored in a manner similar to the example of FIG. 2A. However, the database effort table may include a different number of columns than the number of columns shown in the example. In the example, each effort has an effort ID, its set of GPS information (eg, GPS coordinates with a respective time stamp), an identifier associated with the user who recorded the effort, the date the effort was recorded, and a speed ( km / h), heart rate (per minute), work rate (watts), and time (hours: minutes). In some embodiments, when effort is compared to a segment, effort GPS information (eg, a series of GPS coordinates with a time stamp) is accessed and used for comparison. In some embodiments, once it is determined that the effort matches the segment, the effort's associated data (eg, speed, heart rate, power, time, elevation, slope) may be (If any) and related data. The aggregated data is then analyzed (eg, to generate a display summarizing the aggregated data).

  FIG. 3 is a flowchart illustrating one embodiment of a process for segment matching in accordance with some embodiments. In some embodiments, process 300 is implemented in system 100.

  In step 302, a segment is defined. In some embodiments, the segment is defined by the user selecting start and goal points along the visual representation of the effort (eg, a series of GPS information with a time stamp) at the user interface. In some embodiments, the effort is recorded by a device with GPS tracking capabilities. In some embodiments, a segment is defined by the user selecting a series of points on a map (eg, supported by third party map software such as Google Map) at the user interface. In some embodiments, the segments are defined (eg, by an administrator of the segment matching server) using known features (eg, elevation and average slope) of the geographic path. The defined segments are stored in one or more databases. In some embodiments, the defined segments are converted to an abstract form (eg, a set of minimum bounding rectangles) and stored in the abstract form. In some embodiments, the database in which the segments are stored is organized based on the R-tree index.

  In step 304, the effort that matches the segment is determined. In some embodiments, for a defined segment, information about stored effort is accessed and compared to the segment. In some embodiments, the effort is stored as a set of GPS information along with a timestamp (and associated data such as various measures of athletic performance). In some embodiments, stored effort GPS information is accessed and converted to the same form (eg, minimum bounding rectangle) as the segment prior to comparison. In some embodiments, the stored effort is compared to the segment to determine a subset of stored effort that matches the segment. Relevant data for a subset of stored effort determined to match the segment is obtained and aggregated (eg, from the same database storing the effort). The aggregated relevant data is analyzed, and in some embodiments, the analysis results are presented in a table (eg, a rank table) and / or an image.

  FIG. 4 is a flowchart illustrating one embodiment of a process for defining segments based on effort, according to some embodiments. In some embodiments, process 400 may be implemented using system 100. In some embodiments, process 400 may be used to perform step 302.

  In step 402, a visual representation of the effort is presented. In some embodiments, an effort is a series of GPS information with a time stamp recorded by a device with GPS tracking capabilities. In some embodiments, the visual representation is presented at the user interface. For example, GPS coordinates may be displayed as a solid line or a series of markers on a map (eg, supported by a map application such as Google Maps). In some embodiments, even when the set of GPS information is a set of discrete geographic coordinates, it is possible to estimate the point between the two coordinates when generating a visual representation in the form of a solid line. it can.

  For example, a user (eg, a cyclist) wants to finish cycling and designate at least part of the run as a segment. In this way, the cyclist or other cyclist can track and compare performance on the geographic path referenced by the segment.

  At step 404, a start point selection is received. In some embodiments, the user selects a point along the visual representation in the user interface as the starting point of the segment. In some embodiments, if the selected point has been passed more than once in the effort, a display is generated to show each of the number of times that the selected start point has been passed along the effort. . The user may then select the number of times corresponding to the desired case that the user wants to be a starting point. In some embodiments, the selected start point is stored as its corresponding GPS coordinates (eg, coordinates returned by the API associated with the map application). In some embodiments, the selected start point is stored along with a virtual start line obtained based on the effort's selected start point and one or more other points.

  Returning to the previous example, the cyclist can select a point along his run to designate it as the starting point of the segment. The start point need not be at the start point of the entire segment, but may be any point along the run. The starting point can be thought of as the starting line for the race. When another cyclist (or the same cyclist at a different opportunity) later decides whether or not it has run through the segment, it is determined whether a later run (ie, effort) has passed the start point. .

  At step 406, a goal point selection is received. In some embodiments, the user selects a point along the visual representation in the user interface as the goal point or end point of the segment. In various embodiments, the technique for selecting and storing goal points is the same as that used for the start points. For example, the selected goal point may be stored as its corresponding GPS coordinates and / or with the resulting virtual goal line.

  Returning to the example, the cyclist can select points along his run to designate as the goal point of the segment. The goal point need not be at the very end of the run, but can be any point after the start point. A goal point can be considered as a goal line for a race. When another cyclist (or the same cyclist at a different opportunity) later decides whether or not it has run through the segment, it is determined whether the later run (ie, effort) has also passed the goal point. . In some embodiments, if the defined segment includes a loop, the selected start point and goal point may be the same set of GPS coordinates.

  In step 408, the defined segments are optionally stored. In some embodiments, a defined segment is determined to be similar to an existing segment (eg, in a data store that includes a predefined and / or user-defined segment, such as a segment database) The user is prompted by a corresponding display. In some embodiments, the user can review existing segments and / or choose to discard newly defined segments in light of existing overlapping segments. If the user chooses to discard the newly defined segment, the user can choose to associate his effort with an existing segment and store the data associated with the effort with the existing segment. In some embodiments, if a user-defined segment matches an existing segment, the matched existing segment is stored in a data store that includes a predefined and / or user-defined segment (eg, a segment database). ) Already stored. If there is no existing similar segment, or if one chooses to store the newly defined segment anyway despite possible duplicates, the newly defined segment is stored. In some embodiments, the segments are converted and stored in an abstract form (eg, a set of minimum bounding rectangles). In some embodiments, the newly defined segment may be saved with a name and / or one or more tags (eg, selected by a user). In some embodiments, the stored effort is accessed to match against this segment. If a matching effort is found, the data associated with the matching effort is combined and compared.

  Returning to the example, the cyclist can create a segment using the user interface. The cyclist can also enter the segment name “Old La Honda” to associate the segment with the name of the road on which the segment resides. The cyclist may also receive feedback on past runs made in “Old La Honda” (eg, determined by segment matching). The feedback is which user has run on the segment, who has recorded the fastest time, who has spent the maximum amount of energy at the completion of the segment, and so on. Cyclists can also see how their performance at “Old La Honda” is compared to past runs (eg, the user's performance in the run history for that segment). Where will it be ranked?) Subsequent users can also search for this segment by entering “Old La Honda” in a user interface that supports searching in the segment database. In addition, subsequent users can check whether they have traveled “Old La Honda” by recording their travel and sending the travel to check for a matching segment. If a run is determined to include an “Old La Honda” segment (eg, by segment matching), the performance of subsequent users during the run in that segment is determined by the performance of other users who have run that segment. It can be compared with the history.

  FIG. 5 is a diagram illustrating an example of a user interface for defining segments based on effort, according to some embodiments. In some embodiments, step 402 is performed using the example of FIG. In the illustrated example, the dark line placed on the map is a visual representation 502 drawn from, for example, an effort recorded by a GPS device (eg, a series of GPS information with a time stamp). As shown in the example, the name of the effort for which a segment is selected is shown in area 504 as “Easy Ride Around Lake Fairy”. In some embodiments, the map used in the user interface is supported by a map application such as Google Map. You can interact with the map application through the related API.

  FIG. 6 is a diagram illustrating an example of a user interface illustrating the selection of a segment start point according to some embodiments. In some embodiments, step 404 is performed using the example of FIG. As shown in the example, the map showing the visual representation 502 is zoomed in to the area where the start point is selected. In some embodiments, the starting point can be selected by clicking on a map location. As shown in the example, a marker 602 indicates the selected start point along the effort. As shown in the example, the selected start point has been passed three times at different times along the effort (604, 606, and 608). The user is prompted to select a desired time to be set as a starting point. In some embodiments, the length of the defined segment is determined based on the length of effort between the start point and the goal point, so that the user can select one of a plurality of possible start points. You are prompted to choose. In some embodiments, the selected start point is stored as a set of GPS coordinates. In some embodiments, the selected start point is stored with a virtual start line partially derived from the start point.

  FIG. 7 is a diagram illustrating an example of a user interface illustrating the selection of goal points for a segment in accordance with some embodiments. In some embodiments, step 406 is performed using the example of FIG. In some embodiments, goal points are selected and stored by the same technique used for the start points. As shown in the example, marker 703 indicates a selected goal point (eg, end point) of the segment. In some embodiments, the selected goal points are stored as a set of GPS coordinates. In some embodiments, the selected start point is stored with a virtual goal line derived in part from the start point.

  FIG. 8 is a diagram illustrating an example of a user interface for defining a segment using a series of selections on a map, according to some embodiments. In some embodiments, the illustrated example can be used to perform step 302. In some embodiments, the segment can be defined by making a selection directly on the map of the user interface. In contrast to the segment definition technique as shown in FIGS. 5, 6 and 7, the segment definition technique of the example of FIG. 8 does not require recorded effort. As shown in the example, the user dropped markers 802-818 in order along a route on the map (eg, “Montello Rd”) to show the segment. A set of geographic information for markers 802-818 can be obtained from a map application (eg, Google Maps) and stored as a segment. In some embodiments, the first dropped marker for a segment is considered the start point and the last dropped marker is considered the goal point.

  FIG. 9 is a flowchart illustrating one embodiment of converting a series of GPS information into a minimum circumscribed rectangle (MBR) according to some embodiments. In some embodiments, a set of GPS information (eg, used to define a segment based on recorded effort for a set of selections on a map supported by a map application) is a set. Are converted to the minimum circumscribed rectangle (MBR) and stored for the segment. In some embodiments, the series of GPS information is converted to a set of MBRs and used to query a segment R-tree indexing database stored as a set of MBRs.

  One reason for converting a set of GPS information into a set of MBRs is that, in various embodiments, MBR can be used to perform an efficient bounding box query against an MBR R-tree indexing database. It can be done. In some embodiments, the search input for an R-tree database query (eg, for a defined segment) is an MBR (eg, associated with an effort) and the query overlaps with the entered MBR. Returns the MBR (eg, associated with the segment). In some embodiments, whether an effort is similar (eg, matches) to a segment depends on the degree of overlap of those MBRs found using a bounding box query. In some embodiments, whether a segment is similar to another segment also depends on the degree of overlap of their MBRs.

  In step 902, a series of GPS information is mapped onto a set of tiles. In some embodiments, the set of GPS information is derived from effort recorded by a device with GPS tracking capabilities. In some embodiments, the set of GPS information corresponds to a segment (eg, defined in the user interface).

  Using the well-known technique of universal tiling, the geographical area of interest is divided into substantially uniform tiles. For example, each tile may be 20 meters square. This universal tiling scheme is applied to a series of GPS information to generate a set of corresponding tiles. For example, each tile that includes GPS coordinates (and any tile between two such tiles) is included in the set of tiles. In some embodiments, any two geographic routes covering approximately the same area are mapped to the same set of universal tiles, even though there are minor differences in their respective sets of GPS information.

  Step 904 optionally adds tiles to fill the tiles and provides a path between GPS points that includes a continuous set of tiles. For example, if two consecutive GPS points are not mapped to adjacent tiles, any tile crossed by a line connecting consecutive GPS points can be added to the tile set (eg, GPS points before expansion) Can fill tiles between).

  In step 906, the set of tiles is optionally expanded. In some embodiments, the set of tiles can be expanded to include adjacent tiles to compensate for differences in GPS data. For example, if the eight tiles adjacent to each tile in the tile set made in step 902 are not already included, those tiles can be included in the tile set. However, the set of tiles can be expanded in other suitable ways.

  In step 908, a set of tiles is grouped into a set of MBRs. In some embodiments, tiles that are close to each other in the set are grouped into one MBR. In some embodiments, each dimension (eg, height, width) of the MBR is an entire tile or tiles. For example, to group a set of tiles into a set of MBRs, the sets of tiles are first combined into a set of non-overlapping rectangular boxes. In one approach, horizontally adjacent cells are combined to produce a set of boxes that are wide and have the height of one tile. Each box is then compared to the boxes in the bottom row and combined with any boxes that have the same width and horizontal position. The resulting set of boxes is the desired set of MBRs. However, the method of grouping one set of tiles into one set of MBRs is not limited to this example.

  In some embodiments, each MBR is identified by its four corner coordinates (eg, in a tiling scheme). In some embodiments, the set of MBRs is stored in a database for the segment. For example, the MBRs in the set can be stored in a row of the R-tree indexing database table. The MBRs in the set may be stored with an identifier associated with the segment they represent.

  However, in some embodiments, the segments may be stored as a corresponding set of GPS data points (rather than being stored after being converted to MBR).

  FIG. 10A is a diagram illustrating an example of converting a series of GPS information into a set of MBRs according to some embodiments. In some embodiments, the example of FIG. 10A is the result of applying process 900 to a series of GPS information. In the illustrated example, the recorded bicycle run includes a set of GPS coordinates, which are indicated by small black circles. Each tile of the universal tiling scheme that includes GPS coordinates is included in a set that includes a tile to which GPS information is mapped and any tile that intersects (crosses) a line segment connecting successive GPS points. In the illustrated example, the tiles included in the tile set are shaded. Eight tiles adjacent to each tile in the set are also included in the expanded tile set (if no tile was previously included). The expanded set of tiles is then grouped into 4 MBRs (MBR1, MBR2, MBR3, and MBR4). In the illustrated example, each MBR is blacked out. Each MBR may be identified by a set of coordinates (x1, x2, y1, y2) that represent four corners (eg, in a tiling scheme). If a series of GPS information is intended to define a segment, a corresponding set of MBRs may be stored in a table of the R-tree indexing database along with the segment identifier in some embodiments.

  FIG. 10B is a diagram illustrating an example of an entry in a database table for storing segment information according to some embodiments. In some embodiments, the database is an R-tree indexed database. For example, the database can be MySQL, Oracle, or Postgres. In some embodiments, the example of FIG. 10B includes a set of stored MBRs created in the example of FIG. 10A. In some embodiments, each segment in the segment database is stored with an alphanumeric identifier. Assume that the example of FIG. 10A has created a set of MBRs for a segment having the identifier “Old_La_Honda”. As shown in the example of FIG. 10B, each MBR is stored with its segment identifier, its four coordinates, and occupancy. In the example of the figure, the occupation ratio is a ratio of the number of tiles associated with the segment and included in the MBR to the number of tiles associated with the segment. In some embodiments, the occupancy may be expressed as a percentage. For example, as shown in FIG. 10A, there are 26 shaded tiles, ie, 26 tiles associated with the segment “Old_La_Honda”. Since 6 of these 26 tiles are included in MBR1, the occupancy entry of MBR1 in the database is “6/26”.

  The example of FIG. 10B contains only four entries for a segment (an entry for each MBR in the set), but an actual segment may contain thousands of entries in the database, depending on the length of the path. In some embodiments, the database entries for storing segment information may include a different number of columns than shown in the example of FIG. 10B. In some embodiments, the segment information set stored in the database includes all effort (eg, effort from the effort database) and associated data of the effort determined to match the segment. That way, when a segment is retrieved from the database, athletic performance (eg, represented by matched effort and their associated data) can also be quickly accessed.

  FIG. 11A is a flowchart illustrating one embodiment of a process for searching for a matching segment in a segment database, according to some embodiments.

  In some embodiments, the segments are stored as a set of MBRs in the R-tree indexing database. In some embodiments, the segments are stored as a set of GPS data points in the database.

  In some embodiments, to determine whether a query input (eg, a geographic route represented by a series of GPS data points) matches a predefined segment of the segment database, to the segment database The query is executed. As used herein, a match rate between a series of GPS information (eg, belonging to an effort) and another series of GPS information (eg, belonging to a segment) exceeds a certain threshold. In the event that the GPS information matches.

  In step 1102, a series of GPS information is converted as necessary. In some embodiments, the set of GPS information is extracted from an effort (eg, an effort recorded by a device with GPS). In some embodiments, the GPS information is a series of continuous GPS data points. In some embodiments, the segments are stored in an abstract form, such as a set of MBRs. When a segment is stored as a set of MBRs, a series of GPS information is also converted into a set of MBRs. In some embodiments, since the segments are stored as a set of GPS data points, the GPS information need not be converted to another form.

  In step 1104, the segment information is queried using the GPS information. In some embodiments, the database query returns a segment portion (eg, GPS data point, MBR) similar to a set of GPS information.

  In some embodiments, the segments are stored as a set of MBRs in the R-tree indexing database. For example, to perform a search in the database, a bounding box query is executed against the R-tree indexed database using MBR converted from GPS information. The query returns an MBR that overlaps with the input MBR. Overlapping MBRs are considered similar. For duplicate MBRs, each entry can be returned from a database table (eg, table 1000 in FIG. 10B). Referring to table 1000, in this example, it is assumed that MBR1, MBR2, and MBR3 (all belonging to segment “Old_La_Honda”) are determined to overlap. Thus, each of MBR1, MBR2, and MBR3 can be analyzed so that analysis of those entries (eg, analysis to determine whether the set of input MBRs matches the segment “Old_La_Honda”) can be performed. Rows can be returned. In some embodiments, duplicate MBRs associated with more than one segment may be returned.

  In some embodiments, the segments are stored as a set of GPS data points in the database. Similar segments can be found in the database using various search techniques to determine a similar set of GPS data points (eg, within acceptable limits). In one example of such a technique, each GPS data point in the database is assumed to include a tolerance area indicated by a radius of a selected length (eg, 50 meters). Each point included in the series of GPS information is also assumed to include a tolerance region indicated by a radius of a selected length (which may be the same length as the radius of the points in the database). As a result, each GPS data point can be thought of as extending over an area within a circle. Subsequently, the circular area of each point in the series of GPS information is used to search the database for overlapping circles associated with GPS data points (associated with the segment). In some embodiments, database GPS data points corresponding to overlapping circles may be returned. In some embodiments, GPS data points associated with more than one segment may be returned.

  In some embodiments, searching for similar segments using a series of GPS data points requires more computation time and / or resources than are required to use the MBR and R-tree indexing databases. It is necessary.

  In step 1106, the query results are analyzed. In some embodiments, the query results are used to determine whether a set of GPS information matches a segment of the database. In some embodiments, a calculation is performed to determine a match rate between the set of GPS information and the returned one or more segments.

  In some embodiments, if the segment is stored as an MBR, the match rate is determined using the returned MBR. In some embodiments, the rate of matching between a set of GPS information and a segment is calculated based on the ratio of the number of overlapping MBRs in the segment to the total number of MBRs in the segment. If the match rate exceeds the threshold, the geographic route represented by the series of GPS information is considered to match the segment. In some embodiments, the similarity between a set of GPS information and a segment is calculated based on the total MBR occupancy returned. If the total occupancy exceeds the threshold, the geographic route represented by the series of GPS information is considered to match that segment. In some embodiments, the MBR returned as a result of a query (eg, at step 1104) includes a row from each table in the database. Referring to the table of FIG. 10B, in this example, it is assumed that MBR1, MBR2, and MBR3 (all belonging to the segment “Old_La_Honda”) are determined to overlap. Therefore, the respective rows of MBR1, MBR2, and MBR3 are returned. In this example, the similarity between the series of GPS information and the “Old_La_Honda” segment is calculated based on the total occupancy rate of the duplicate MBRs. Since MBR1, MBR2, and MBR3 overlap, the total occupancy (ie 6/26 + 4/26 + 10/26) is 20/26 or about 76.9%. If the match rate threshold is 65%, the series of GPS information is considered to match the “Old_La_Honda” segment. In some embodiments, MBRs may be returned for more than one segment, and the similarity for each of those segments may be determined.

  In some embodiments, if the segment is stored as a set of GPS data points, the match rate is determined based on the number of GPS data points returned by the query. In some embodiments, if the ratio of the number of GPS data points returned by the query to the total number of GPS data points associated with the segment exceeds a certain threshold, the geographic represented by the set of GPS information The path is considered to match the segment. In some embodiments, GPS data points may be returned for more than one segment, and a match rate for each of those segments may be determined.

  In some embodiments, if the match rate between a series of GPS information falls below a threshold (eg, 65%), the geographic path is considered not to match the segment. In some embodiments, there are multiple thresholds within which a set of GPS information may match a segment. In some embodiments, a sequence of GPS information can be considered a gentle match of a segment if it matches the segment with a lower threshold (eg, between 65% and 79%). In some embodiments, a set of GPS information may be considered a candidate for an exact match of a segment if it matches the segment with a higher threshold (eg, between 80% and 100%). In some embodiments, in order to be considered an exact match of a segment, a series of GPS information needs to cross the segment's virtual start and goal lines as well as match the segment with a higher threshold. is there. If a series of GPS information is considered a loose match to a segment, the geographic path (eg, effort) associated with that GPS information does not strictly follow the path referenced by the segment Means that. For example, a cyclist who intends to cycle slowly along the general terrain delimited by segments can deviate slightly from the exact segment. If a series of GPS information is considered an exact match to a segment, it means that the geographic path associated with that GPS information has followed the path referenced by the segment exactly. For example, a cyclist who intends to compete for time (or another performance measure) across a segment against his records or the performance of others needs to follow the area bounded by the segment more closely. Cyclists who compete for time must also cross the virtual start line and goal line of the segment (or the segment loops) to ensure that it runs the entire length (not just a part) of the segment. If so, the entry point that entered the loop segment must be passed once more).

  FIG. 11B is a flowchart illustrating one embodiment of matching effort to a segment according to some embodiments. In some embodiments, process 1150 is used to perform step 1106 according to some embodiments.

  Assume that at the start of process 1150, step 1104 has already been performed and the query returned a similar portion of the segment (eg, duplicate MBR or GPS data points within a given tolerance).

  In some embodiments, the process of matching an effort to a segment includes step 1152, ends after step 1154 (determining a loose match), and does not include an exact match determination. In some embodiments, the process of matching effort to a segment includes steps 1155 through 1160 (exact match determination) but does not include a loose match determination. In some embodiments, the process of matching the effort includes determining both a loose match and an exact match of the effort for the stored segment.

  In step 1152, it is determined whether the match rate between the effort and the segment exceeds a first threshold. If the match rate is less than the first threshold (eg, the match rate is less than 65%), the effort is considered not to match the segment and the process 1150 ends. If the match rate exceeds the first threshold (eg, the match rate exceeds 65%), the effort is considered a loose match for the segment at step 1154 and control proceeds to step 1155.

  In step 1155, it is determined whether the match rate between the effort and the segment exceeds a second threshold. If the match rate exceeds the second threshold (eg, the match rate is greater than 80%), the effort is considered to be an exact match candidate for the segment and control proceeds to step 1156. If the match rate is less than the second threshold (eg, the match rate is between 65% and 79%), the effort is considered not a close match (only a loose match) and the process is finish.

  In step 1156, it is determined whether the effort crosses the start line and goal line of the segment. If crossing both the start line and the goal line, the effort is considered to be an exact match of the segments at step 1160. However, if one or both of the lines are not crossed, the process ends and the effort is considered not a close match (only a loose match).

  In some embodiments, if the effort is compared to a segment forming a loop (eg, Central Park in New York City), step 1156 is performed because no start line or goal line is created for the loop segment. It is not necessary. Instead, in some embodiments, for an effort deemed a candidate for an exact match of a loop segment, the entry point associated with the location where the effort first intersected the loop segment is first determined. If it is then determined that the effort has passed the loop segment's determined entry point a second time, the effort is considered to be an exact match of the loop segment.

  FIG. 12 is a diagram illustrating an example of creating a virtual start line according to some embodiments. In some embodiments, a virtual start line is created for the defined segment. In some embodiments, when a segment is defined (eg, by process 400) using recorded effort, a virtual start line is derived from the GPS information and the selected start point. In some embodiments, if a segment forms a loop, no start line or goal line is created for the segment.

In the example of FIG. 12, the recorded effort is represented by a series of continuous GPS coordinates P1 (t0), P2 (t1), P3 (t2), P4 (t3), and P5 (t4). . Point P1 (t0) is passed at a time earlier than P2 (t1), P2 (t1) is passed at a time earlier than P3 (t2), and so on. The start point is selected at position 1202. The selected start point is placed before passage of P1 (t0) after passing through and P 2 (t1). Since the next GPS coordinate in the series of GPS coordinates is unpassed P2 (t1), a linear path 1208 is drawn from P2 (t1) to the selected start point. The virtual start line 1206 is selected such that its center overlaps the center of the linear path 1208 between the selected start point and P2 (t1). In this example, virtual start line 1206 intersects linear path 1208 at an angle of 90 degrees, but may intersect at other angles. The length of the virtual start line may be set to any appropriate length (for example, 100 meters). In some embodiments, the virtual start line may be stored in the segment database along with the segments associated with it. In some embodiments, the virtual start line may be stored as coordinates only at the ends of the line (eg, because the line can be reproduced by drawing a straight line between the two coordinates). In some embodiments, the virtual start line may be stored as a dense series of GPS coordinates along the line.

  In some embodiments, a goal line can be created and stored similar to the techniques described above.

  In some embodiments, a start (or goal) line is considered crossed if it can be determined that a series of effort GPS information intersects the line. For example, even if a series of GPS information is formed of discrete points, if two consecutive points are found on different sides of the line, the associated path is considered to cross the line. In some embodiments, if one point in a series of GPS information is known to be close to a line (eg, within a given distance), actual physical activity, even if the corresponding record did not suggest A series of GPS information extrapolations can be performed based on known relevant data (e.g., speed, slope, heart rate) for the effort to determine whether or not has crossed the virtual line. For example, some GPS enabled devices record GPS information at a different frequency than others. Therefore, depending on the type of recording device used, some differences can occur between the recorded GPS information. However, extrapolating GPS information based on other known data can compensate for at least some of the differences and make it more certain that athletes who actually cross the line will be allowed to do so. .

  FIG. 13 is a flowchart illustrating one embodiment of a process for determining a matching effort according to some embodiments.

  In step 1302, the effort is compared to the segment. In some embodiments, the segment is already defined. In some embodiments, the segments are stored in a database. In some embodiments, the segments are stored as a set of MBRs. In some embodiments, the segments are stored as a series of GPS data points. In some embodiments, the effort is obtained from a stored past effort database.

  In various embodiments, the effort is compared to the segment to determine a match rate. In some embodiments, GPS information associated with the effort is obtained (eg, from a database). In some embodiments, if the segment is stored as a set of MBRs, the effort GPS information is also converted to a set of MBRs and then compared. In some embodiments, if the segment is stored as a set of GPS information, the effort GPS information need not be converted.

  In some embodiments, an effort is considered to match a segment if the match rate exceeds a threshold. In some embodiments, the effort may match a segment at two different levels: a loose match and an exact match. If the effort matches a segment with a lower threshold, the effort is determined to be a loose match, suggesting that the similarity of the geographic path between the effort and the segment is lower. It is determined that the effort matches the segment at the higher threshold and that the effort crosses both the start line and goal line of the segment (or if the segment forms a loop, the effort If it is determined that the entry point was passed for the second time, the effort is an exact match. In some embodiments, an exact match indicates a high degree of similarity of geographic paths between (at least a portion of) the effort and the segment. In some embodiments, an identifier associated with the effort that matches the segment is stored with the segment. In some embodiments, the identifier of the segment that matches the effort is stored with the effort.

  In step 1304, it is determined whether there is more effort to compare with the segment. In some embodiments, all stored effort is compared to the segment. In some embodiments, only a subset of the stored effort is compared to the segment. In some embodiments, all effort compared to a segment is associated with one user. In some embodiments, the effort compared to the segment is associated with more than one user.

  In step 1306, data associated with the matched effort is aggregated. In some embodiments, for effort considered to match a segment (eg, as a loose match or an exact match), their associated data (eg, heart rate, speed, heart rate, work rate, time) is ( Access and aggregate (for example, in an effort database). For example, the aggregated data may be temporarily stored in another database.

  In step 1308, the aggregated data is analyzed. In some embodiments, the calculations are performed using the aggregated data of the matched effort. For example, average heart rate, average speed, average time, average power, and / or average slope can be calculated. In some embodiments, each effort's related data set is compared to each other effort's related data set to create a sorted list of matched efforts (eg, the list is related Can be sorted based on any one measure of the data). For example, the sorted list may include a list of efforts arranged in descending order from the fastest time. Alternatively, in another example, the sorted list may include a list of efforts arranged in ascending order from highest power. For example, the sorted list may include a list of recently recorded efforts. In some embodiments, the aggregated data analysis results may be displayed (eg, in a user interface). The display may include a table and / or an image.

FIG. 14 is a diagram illustrating an example of a display of data analyzed for matched effort, according to some embodiments. In some embodiments, the example of FIG. 14 is displayed for a selected segment for which a matching effort has been determined. In other words, each effort matched to a segment implies that each effort was considered to have followed the geographic path referenced by the segment. The example of FIG. 14 may be displayed on a user interface (eg, of a device). In the example, since the physical activity associated with the effort is cycling, each effort will be referred to as running. Section 1402 includes a list of recent rides including the user, date, heart rate (HR), work rate (Watts), and time (Time). Section 1404 is a list of runs sorted by time, with the fastest time finishing the segment listed first. List of sections 140 4 is an example of the "standings".

  By defining a geographic path as a segment, the segment can be easily referenced for comparison of athletic performance on that path. In some embodiments, the user can define segments in the user interface using GPS data recorded from his own physical activity. In some embodiments, the user can define a segment in the user interface by making a selection on the map. No matter how the segment is defined, once defined, the stored history of physical activity (eg, effort) can be accessed and matched to the segment. Matching effort related data may be aggregated and presented in a table or image representing all or part of all physical activity associated with the segment. In some embodiments, the same user or another user can later check whether the recorded activity includes or matches a defined segment. Subsequent checks may benefit the user from automatically matching their recorded activities against the defined and stored segments without having to know exactly where the segments begin or end.

  Analyzing based on the user's GPS location and other data points of the user using conventional systems cannot support a real-time feedback comparison with other users during physical activity. This is because such analysis could not be performed before the user's GPS device could be connected to the computer.

  It is disclosed to provide real-time feedback on current activity associated with a segment. In various embodiments, while a user is performing a current activity (eg, cycling, running) that matches one or more segments, the defined and stored segments are used in real time for the user. Feedback can be generated. In some embodiments, “real time” includes providing feedback or communication to the user at the device while the user is still in the current activity (ie, feedback is ongoing for the current activity). In between, provided to the user). In various embodiments, the feedback is provided to the user during the user's current activity without requiring input by the user for feedback. Instead, parameters can be set by the user or by default settings that indicate when and in response to which event, what type of content is provided during the user's activities, and so on. Examples of types of feedback include comparing a user's current performance so far in a matched segment with the user's own historical performance data or other users' historical performance data in that segment, nearby users and / or It may include segment detection as well as an indication of the user's individual performance regarding the user's performance in previous segments. As a result, the user is based on the user's current performance on one or more matched segments without having to actively initiate segment matching / discovery or comparison etc. while performing the activity. You can enjoy feedback and other information about the matched segments. For example, during physical activity, the user may not be interested, or it may not be practical for the user to manually start receiving feedback regarding the user's current activity.

  FIG. 15 is a diagram illustrating one embodiment of a system for providing real-time feedback during current activity associated with a segment, according to some embodiments. In this example, the system 1500 includes a device 1502, a device 1504, a network 1506, and a segment matching server 1508. Network 1506 includes various high speed data networks and / or telecommunications networks. In some embodiments, the system 1500 comprises at least the components of the system 200 in addition to additional components and / or functions.

  In some embodiments, a user can carry one or both of device 1502 and device 1504 when performing physical activity. For example, one or both devices may be worn on the user's body (eg, strapped to the user's arm) or attached to a vehicle (eg, a bicycle) used by the user during physical activity. Also good.

  One or both of device 1502 and device 1504 may record location information (eg, GPS data) and / or other data related to physical activity (eg, speed, heart rate). Examples of device 1502 and / or device 1504 include GPS devices (eg, Garmin Forrunner 110, 205, 301, 305, 310XT, 405, 405CX, and Garmin Edger 305, 605, 705, 500, etc.) Devices), mobile phones, computers, tablet devices, and / or other general-purpose computer devices, such as smartphones (eg, Android devices or Apple iPhone devices) with GPS recording applications (eg, MotionX, Endomondo, and RunKeeper) And / or dedicated computer devices, which are typically Comprising a processor for general, a memory or other storage element, the network or input and output (I / O) capabilities and, the, the interface for the integrated GPS function or support or GPS device or GPS function.

  In some embodiments, device 1502 has the capability to exchange data with a remote server (such as segment matching server 1508) via network 1506, but does not have the capability to communicate with device 1504. For example, the device 1502 can communicate with the device 1504 using a short-range protocol for wireless communication such as Bluetooth (registered trademark) or using a wired connection. In such an embodiment, the device 1504 has a function of exchanging data with the segment matching server 1508 via the network 1506. Accordingly, the device 1502 can exchange data with the segment matching server 1508 via the device 1504. For such embodiments, device 1502 may be a non-network device that records the user's location information and / or other data related to physical activity and then transmits the recorded information to device 1504. For example, the device 1504 can receive the recorded information from the device 1502 (eg, using an installed application) and then send the recorded information to the segment matching server 1508 (smartphone or tablet Device). Further, information (eg, feedback data) transmitted from the segment matching server 1508 is received by the device 1504 and then transmitted to the device 1502.

  In some embodiments, device 1502 has the capability to send and receive data via network 1506 (ie, 1502 is a network device), and device 1504 is optionally included in the system. In an embodiment where the device 1502 can record location information and / or other data related to physical activity and send and receive data over the network 1506, the device 1502 may be without the device 1504. For example, the recorded information can be transmitted to the segment matching server 1508, and the analysis result of the recorded information can be received from the segment matching server 1508, for example.

  Two or more devices (such as the combination of device 1502 and device 1504 described in the example above) can be used to record information related to physical activity and communicate with the segment matching server 1508, although the drawings and In the description, for the sake of illustration, it is described that only one device (device 1502 having a network function) is used to record information and communicate with the segment matching server 1508.

  In various embodiments, the device 1502 (or its application) may record location information (eg, GPS data) and / or other data related to physical activity while the user performs physical activity. Composed. In some embodiments, the physical activity that the user is currently performing will be referred to as the “current activity”. Examples of physical activity include cycling, running, and skiing. In some embodiments, the GPS information includes a series of continuous and discrete GPS data points (eg, latitude and longitude), with a time stamp for each point. In some embodiments, the relevant data includes elevation, heart rate, power / wattage (eg, energy consumed), time, speed (eg, average and / or maximum speed per segment and / or route, For example, the average speed may be derived from time and GPS information), but is not limited thereto. In some embodiments, at least some of the relevant data will be referred to as “performance data”. Related data can be recorded at various granularities. For example, the relevant data may correspond to each GPS data point, the entire activity (eg, the relevant data includes an average of measurements), or a portion of the activity.

  In some embodiments, prior to using the device 1502 during physical activity, the device 1502 parameters (or to determine how the device 1502 interacts with the segment matching server 1508 before or during physical activity) , A user account associated with the application of the device 1502 is set. The parameters of device 1502 (or the user's account associated with the application of device 1502) can be set by the user and / or by preset settings. In some embodiments, parameters associated with the device 1502 may be set to determine what data is received from the segment matching server 1508 at the device 1502 before the user begins physical activity. In some embodiments, the parameters can filter out data that is not of interest to the user or identify the type of data that is of interest to the user. For example, data obtained from the segment matching server 1508 prior to physical activity is stored locally on the device 1502 (eg, temporarily stored in a cache or otherwise) and recorded by the device 1502 during physical activity. Can be used to process the information. In some embodiments, parameters associated with device 1502 are set to determine when (eg, how often) and what type of data is exchanged with segment matching server 1508 during physical activity. May be. Parameters associated with the device and / or user may be set, for example, on device 1502 and / or set elsewhere and downloaded to device 1502. In some embodiments, a copy of the configured parameter is also sent to the segment matching server 1508 and maintained. For example, data transmitted from device 1502 during physical activity may include recorded GPS data and other data related to the user's current activity so far. Also, for example, data received from the segment matching server 1508 at the device 1502 includes various types of real-time feedback based at least in part on the processing of recorded GPS data and other data transmitted from the device 1502. In some embodiments, the device 1502 continuously (eg, periodically) sends new and / or updated recorded information to the segment matching server 1508, which updates the feedback. Data can be continuously returned to the device 1502. In some embodiments, the feedback data includes one or more segments determined to match or approximate recorded information related to the user's current activity. In some embodiments, feedback data is stored for one or more segments determined to match the user's performance in the current activity and the user's current activity (eg, for that user or other users). Includes comparison results with historical or concurrent performance information. In some embodiments, the feedback data includes notifications and invitations related to concurrent activities performed by other users and / or indications of the user's personal performance. Other types of feedback data may be received at device 1502. In some embodiments, at least some of the data (eg, feedback data) received at device 1502 is presented to the user in real time using images, text, and / or audiovisual. For example, the user interface of the device 1502 can display the comparison results from the feedback data, and the audio output of the device 1502 can output a reading of the comparison results.

  In various embodiments, the segment matching server 1508 has the functionality of the segment matching server 106 and additional functionality. In some embodiments, the segment matching server 1508 is configured to determine whether the GPS data received from the device 1502 matches one or more defined segments. For example, the segment matching server 1508 may ensure that at least a portion of the GPS data received from the device 1502 so far crosses at least a portion of the segment (eg, the GPS data is assigned to the currently active user associated with the segment). It can be determined that the received GPS data matches the segment based on the determination that it has crossed the start line). In some embodiments, if it is determined that the location information recorded for a user's current activity matches a segment, the user is on the matched segment (ie, is traveling along that segment). It is estimated to be. In some embodiments, once a matching segment is determined, the segment matching server 1508 can match the matched segment to be used for comparison with current performance data received from the device 1502 based on the user's current activity. Configured to retrieve related stored history or concurrent performance data. The segment matching server 1508 is configured to transmit at least part of the comparison result to the device 1502 as part of feedback data. In some embodiments, the segment matching server 1508 may use other types of feedback (eg, other users) based at least in part on one or more segments that match the received data regarding the current activity of previous users. Notifications and invitations related to concurrent activities and / or personal performance indications about user data). In some embodiments, the segment matching server 1508 is configured to perform segment matching and / or generate feedback data for the user based on parameters set in association with the user. . In some embodiments, the segment matching server 1508 is configured to update the generated feedback data based on GPS data and other related data that is updated over time and received from the device 1502.

  FIG. 16 is a diagram illustrating use of system 1500 while a user performs an activity, according to some embodiments. In the example, user 1600 is performing a cycling activity. Assume that user 1600 is utilizing device 1502 of system 1500 during cycling. Prior to initiating the activity, the user 1600 may send data to the remote server and receive feedback data based on the user's interests, or generate feedback locally at the device during the activity, segment The parameters of the device 1502 regarding the match, other users, comparison type, etc. are already set. When the user 1600 is cycling along the path, the user 1600 does not need to know whether he is traveling along the segment and where the segment is located relative to the user's 1600 cycling path. However, with device 1502, user 1600 may be presented with feedback to device 1502 during user 1600 activity. For example, as shown in the figure, user 1600 may determine which segment user 1600 is currently running (“Old La Honda”) and where user 1600 is currently located (“segment“ Old La ” Feedback data indicating that “25% of Honda” has been reached ”) may be presented at device 1502. The user 1600 continuously updates (e.g., at regular and / or set events) updates and feedback while proceeding along the segment without having to initiate or query feedback during the activity. Other types of feedback data can be received (eg, “Running Old La Honda≡” with the lowest heart rate ever!). The feedback that the user 1600 receives during physical activity can sometimes be a motivating or other factor for the user 1600 to change his performance over the rest of the segment. For example, if user 1600 receives feedback such as “3 seconds before the top of“ Old La Honda ””, if the goal of user 1600 is to speed up to catch up with the top of the segment or Motivated to overtake. As shown in this example, utilizing the system 1500 during a user's current activity can help inform the user in real time about information about the user's performance that the user could only know after the activity ended.

  FIG. 17 is a diagram illustrating one embodiment of a segment matching server, according to some embodiments. In some embodiments, the segment matching server 1508 is implemented using the example of FIG. As shown in the example, the segment matching server 1508 includes some of the same components (segment database 202 and definition engine 206) as the segment matching server 106 described above, and further includes a configuration parameter database 1702, a feedback engine 1704, an effort. / Includes additional components such as a current activity database 1703 and a matching engine 1708.

  In some embodiments, the configuration parameter database 1702 is configured to store a set of configuration parameters associated with various devices and / or users. In some embodiments, a set of methods in which data (eg, recorded GPS data and related data) is transmitted to segment matching server 1508 and how data (eg, feedback) is received from segment matching server 1508. Are set by the user for a specific user and / or a specific device. In some embodiments, the set of parameters includes parameters set by the user and preset parameters (eg, parameters determined by a manufacturer of a device such as device 1502). Examples of parameters are whether and when data related to a segment is downloaded to the device, when it is downloaded, an identifier associated with the segment that a particular user is interested in, and a particular user compared to his own performance Identifiers associated with other users who have the performance data that they want to do (eg, historical or concurrent performance data), the type of comparison between the user's performance data related to the current activity and another set of performance data The frequency with which recorded GPS and other data is transmitted from the device, one or more triggers for transmitting recorded GPS and other data to be transmitted from the device, interest in conserving device battery life Once the user is interested The range of time related to the type of personal outcome, whether or not a particular user's performance is shared on one or more social media / network platforms, and when to share, simultaneity among multiple users (e.g. The definition may include a range of time or distance at which at least two users performing physical activity are considered concurrent with each other). In some embodiments, a set of parameters is stored with an identifier associated with the user and / or device for which the setting was made.

  In some embodiments, the effort / current activity database 1703 has the functionality of the effort database 204 and additional functionality. In some embodiments, in addition to storing the recorded effort data as described above for the effort database 204, the effort / current activity database 1703 is for the user's current activity (ie, ongoing activity). The recorded GPS data and related data are also stored. In various embodiments, the GPS data and related data recorded for the user's current activity is new and / or updated GPS data and related data recorded for the user's current activity over time as the user proceeds further with the current activity. And updated and / or added. For example, during the current running activity of user “Barry”, GPS data and related data recorded by time t 0 may be sent to segment matching server 1508 and stored in an entry in effort / current activity database 1703. Then, the GPS data and related data recorded by Barry's current running activity by time t1 thereafter (ie, only data recorded from time t0 to time t1) is sent to segment matching server 1508 for effort. / Added to the corresponding entry in the current activity database 1703.

In various embodiments, the matching engine 1708 has the functionality of the matching engine 208 and additional functionality. In some embodiments, the matching engine 1708 may continuously (eg, periodically) record new or updated GPS data and other data recorded on a device, such as device 1502, over time as the user progresses with physical activity. And / or upon various configured trigger events). In some embodiments, the matching engine 1708 uses previously received GPS data from the device to determine whether the GPS data crosses at least a portion of one or more defined segments. For example, the matching engine 1708 may use the GPS data recorded for the current activity if the GPS data indicates that at least a portion of the recorded GPS data has crossed the virtual start line defined for the segment. It can be determined that the data matches the segment (ie, the user is on or very close to the segment's path). Defining a virtual start line for a segment and determining whether the virtual start line has been crossed can be performed using the technique described above with reference to FIG. 12, eg, recorded Instead of using the GPS information associated with the effort, the GPS data previously recorded for the current activity is used to determine whether two consecutive points are on different sides of the virtual start line. If it is on a different side, the current activity is determined to match the segment because it is determined to have crossed the virtual start line of the segment. In another embodiment where the segments form a loop, instead of defining a virtual start line for the loop segment, the GPS activity recorded for the current activity is used to determine that the current activity (e.g., at least part of the loop segment It can be determined whether or not a loop has been entered. If it is determined that the GPS data recorded for the current activity has crossed at least a portion of the loop segment, it is determined that the current activity matches the loop segment. In some embodiments, one or more segments can be determined to match the GPS data recorded for the current activity. In some embodiments, as new and / or updated GPS data recorded for current activity is received over time, the matching engine 1708 may use the new and / or updated GPS data to Determine whether the GPS data associated with the current activity still matches the segment previously determined to match that current activity (ie, whether the user is still on the path associated with that segment) can do. If it is determined that the user's current activity still matches the segment, the matching engine 1708 can determine how far the user has advanced along the segment. For example, based on GPS data recorded for the user's current activity received so far, the matching engine 1708 may determine that the user has reached 70% of the segment. In some embodiments, the matching engine 1708 uses a set of configured parameters associated with the currently active user (retrieved from the configuration parameter database 1702) as a segment that the user wishes to match. Is configured to determine the identified segment or segments. The matching engine 1708 can then match the GPS data of the user's current activity with only the segments that are of interest to the user, rather than all available / defined segments in the database. In some embodiments, the matching engine 17 08 is configured to send an identifier associated with the matched segment or segments to the feedback engine 1704.

  The feedback engine 1704 uses a set of configured parameters associated with the user and data about at least one segment consistent with the user's current activity to provide feedback data to be transmitted to the device being utilized by the user. Configured to determine the type. In some embodiments, the feedback engine 1704 retrieves a set of configured parameters associated with the user's identifier from the configuration parameter database 1702. In some embodiments, the feedback engine 1704 receives an identifier associated with the segment that matches the user's current activity from the matching engine 1708. In some embodiments, using the received identifier associated with the matched segment, the feedback engine 1704 may provide historical data regarding the effort of the user and / or other users that matched the same segment to the effort / current activity. It is configured to retrieve from the database 1703. In some embodiments, the feedback engine 1704 is configured to retrieve from the effort / current activity database 1703 data obtained concurrently with respect to the current activity of other users that matched the segment. For example, other user's current activity data may be determined to be synchronized with the user based on the definition of simultaneity in the retrieved set of configured parameters. In some embodiments, the feedback engine 1704 uses the retrieved set of configured parameters to allow at least any subset of the retrieved data for the matched segment to be associated with the user's current activity related data ( Decide if you want to compare with performance data. For example, the user's configured parameters would allow the user to compare the user's performance data related to the user's current activity with his friends Carrie, Daniel, and Eric's history or concurrent performance data on the matched segment. It may suggest that you think. In some embodiments, the feedback engine 1704 can use the set of retrieved configured parameters to determine what type of comparison to perform on the retrieved history and / or concurrent data. For example, the user's pre-configured parameters indicate that the user wants to receive feedback data about the rank table that includes his own performance data and performance data related to friends Carrie, Daniel and Eric. Yes. In some embodiments, the feedback engine 1704 sends a notification that the user has detected a segment of interest and / or another user nearby (as suggested by the retrieved set of configured parameters). It is configured to In some embodiments, the feedback engine 1704 communicates with a third party operated social network to view the user's specific performance that the user has achieved in the current activity and / or an updated progress report of the user's current activity. It is configured to post the display to a social network platform. In some embodiments, the feedback engine 1704 may be configured to provide feedback data other than the types described above.

In some embodiments, device 1502 comprises at least some or equivalent functionality of segment database 202, definition engine 206, effort / current activity database 1703, matching engine 1708, configuration parameter database 1702, and feedback engine 1704. The device 1502 may provide real-time feedback at the device 1502 without having to interact with the segment matching server 1 5 08 during user activity. In some embodiments, the device 1502 prefetches segment data from the segment matching server 1508 and stores it locally before the user performs physical activity. In doing so, feedback data (eg, data that includes at least the matched segments) may be generated based on the prefetched data during the execution of the activity.

  FIG. 18 is a flowchart illustrating one embodiment of a process for providing real-time feedback during current activity associated with a segment, according to some embodiments. In some embodiments, process 1800 is implemented in system 1500. In some embodiments, process 1800 is performed at device 1502 of system 1500.

  In step 1802, a segment associated with the user's current activity is determined based at least in part on at least a portion of the location information recorded so far. In some embodiments, location information (eg, GPS data) is recorded for the user's current activity (eg, cycling or running) while the user is performing the activity. In some embodiments, relevant data of the user's current activity is also recorded while the user is performing the activity. At least some of the relevant data (eg, speed, heart rate, work rate / watt, rhythm) is related to user performance during the current activity. Over time, additional GPS data and related data are recorded for the user's current activity. At some point during the user's current activity, at least a portion of the recorded GPS data is used to determine a segment associated with the user's current activity. In some embodiments, the segment associated with the user's current activity is a segment that matches at least a portion of the location information previously recorded for the user's current activity.

  At step 1804, real-time segment performance information related to the user's current activity on the segment is communicated. In some embodiments, the type and method of performance information communicated is determined based on a set of configured parameters associated with the user and / or the device that generated the location information. In some embodiments, once a segment is determined (eg, by segment matching), the data stored in association with that segment is retrieved. In some embodiments, the retrieved data may include historical performance data for related segments (eg, matched segments) of users (including current active users and other users), and on current segments. And concurrent performance data for related segments of other users at the same time. In some embodiments, the performance data recorded for the user's current activity so far in the determined segment is compared with the corresponding portion of the retrieved data associated with the determined segment, and the comparison result is communicated. Performance information. For example, the comparison result may be generated by comparing the user's historical performance data at the determined segment with the performance data of the user's current activity at that segment. In some embodiments, the performance information includes the user's current progress along the segment, and is at least in part in location information recorded so far and data identifying a geographic location along the segment. To be determined. In some embodiments, the performance information includes indications regarding the achieved personal outcome based on the recorded location information and relevant data of the user's current activity. In some embodiments, performance information (instead of or in addition to other information) related to the user's current activity in the determined segment is the user interface (eg, of the device that generated the location information and related data). Or can be communicated through audio and / or video output.

  In some embodiments, information about segments close / adjacent to the current location of the user's current activity is also communicated. In some embodiments, segments that are close to or adjacent to the user's current location include segments that do not match the user's current activity but are within a specified distance to the user's current location. For example, the user may be interested in recommended segments that are close to the user's current location and / or the segment the user is currently traveling (eg, within a specified distance, such as within a 10 mile radius). Informing the user of nearby segments can help the user find a segment that did not know about the presence or that did not know about the current location. In some embodiments, a filter parameter is set to detect / notify / recommend nearby segments for the user so that only segments that meet one or more criteria are detected and recommended to the user. Can be done. For example, criteria for detection of nearby segments may include one or more of the following. For segments that are within a certain distance to the user ’s current location, that suggests that the user is interested, or that suggest that the user is interested (for example, geography, distance, elevation, Segments determined to be similar (based on and / or other criteria) and / or segments determined to be popular among one or more other users. In some embodiments, detection of nearby segments may be performed periodically and / or during other events throughout the user's current activity because the current location changes as the user performs the current activity. For example, as a user proceeds with current activity, they may enter new and / or different geographic regions, where different sets of nearby segments can be detected and recommended to the user. In some embodiments, such events are determined so that as each event occurs during the user's current activity, a determination of nearby segments can be made based on the established criteria and the user's updated current location. Can be set. For example, an event may be a 10 minute progress from a previous decision, or a progression of 5 miles from a previous decision.

  FIG. 19 is a flow diagram illustrating one embodiment of a process for setting parameters related to sending information recorded at a device to a remote segment matching server, according to some embodiments. In some embodiments, process 1900 is implemented in system 1900. In some embodiments, process 1900 is performed prior to execution of process 1800.

  The process 1900 may include a segment matching server (such as a segment matching server 1508) from which recorded GPS data and related data (eg, performance data) are recorded so that the server can receive the data and perform analysis. ) Can be used to set relevant parameters. In some embodiments, the selection of process 1900 may be entered by a user at a user interface associated with a device, such as device 1502. In some embodiments, the parameters set by the process 1900 can be stored and utilized during user activities. In some embodiments, the parameters for data transmission may be more or less than those shown in the examples. In some embodiments, based on configured parameters, the frequency with which the device sends recorded data to the segment matching server can be dynamic through the user's current activity. In some embodiments, if the parameters set for data transmission define higher frequency data transmission, the data analysis results returned from the server (ie, feedback data) are more frequently / detailed. This can increase the power consumption of the device. However, if the data transmission frequency is lowered, the frequency of feedback data from the server is lowered, but the power consumption of the device is reduced.

  In step 1902, it is determined whether an event that triggers transmission of data is set. If a trigger event is set, control proceeds to step 1904. Otherwise, control proceeds to step 1906. At step 1904, one or more trigger event definitions are received. For example, a trigger event may be associated with an interruption of the user's current activity that may indicate that the user is resting and / or that something unusual is happening with the user's current activity.

  In step 1906, it is determined whether data transmission is performed periodically. If the data is sent periodically, control proceeds to step 1908. Otherwise, control proceeds to step 1910. At step 1908, a period definition is received. For example, the time period can be set so that data is sent to the server every 10 seconds.

  In step 1910, it is determined whether the transmission of data depends on the interest in saving battery life of the device. If the transmission of data depends on the interest in saving battery life, control proceeds to step 1912. Otherwise, control proceeds to step 1914. At step 1912, one or more definitions associated with battery life saving are received. For example, some level of interest in device battery life savings (eg, from a level that strongly desires battery life savings to a level that is less interested in battery life savings) sends recorded data to the server Can be defined along with corresponding settings for the frequency to do. Thus, for example, a strong interest in saving battery life is associated with sending data to the server relatively infrequently, and a low interest in saving battery life is servering data with a relatively high frequency. Associated with sending to.

  In step 1914, it is determined whether other rules are set. If other rules are set, control proceeds to step 1916. Otherwise, process 1900 ends. For example, rules other than the examples described in steps 1902, 1906, and 1910 can be defined.

  FIG. 20 is a flowchart illustrating one embodiment of a process for prefetching segment data from a server and generating real-time feedback at a device according to some embodiments. In some embodiments, process 2000 is implemented in system 1500.

  Using process 2000, it is determined what data to prefetch from a segment matching server (such as segment matching server 1508) before the start of the user's physical activity, and later in real time locally on the device during the user's physical activity. Such data can be stored on the device so that feedback can be generated. In some embodiments, the process 2000 requires the use of a network connection during a user's physical activity so that GPS data for the activity can be determined, but feedback using data prefetched from a segment matching server. Since analysis for generating data can be performed locally, there is no need to repeatedly transmit recorded GPS data and other data to a remote segment matching server. In some embodiments, process 2000 may consume battery life slower and provide feedback data faster than processes that need to communicate frequently with remote segment matching servers.

  In step 2002, optionally, one or more selections associated with the segment are received. In some embodiments, such selection may be entered by a user at a user interface associated with the device. In some embodiments, step 2002 gives the user an opportunity to select only the segments that the user wants to match before the user performs physical activity (and possibly when the user is ready to begin physical activity). . Accordingly, the selection for the segment received in step 2002 can be used to determine data that includes only such segments, rather than all the segments in which the data is stored.

  In some embodiments, such one or more selections may also be related to segments of interest to the user, such segments being close to the segment during physical activity by the user (eg, within a 10 mile radius, etc.) Detected when in the specified distance range. For example, the user can select segment data related to the segment of interest to the user and prefetch from the segment matching server so that the user is close to such segment during physical activity Be notified at times. For example, later, when the user is performing physical activity, the prefetched data loaded into the device from the segment matching server may indicate whether the user's current activity matches the segment and / or the user's current It can be utilized to determine if there is a segment near the location (eg, periodically and / or every time the user travels X miles).

  At step 2004, data regarding the segment is obtained from the server based at least in part on the one or more selections. In some embodiments, the data regarding the segment identified by the selection includes effort historical performance data determined to match the segment, and geographic information (eg, a set of tiles or MBRs) that defines each of the segments. Including one or both.

  In some embodiments, additional segment data regarding segments other than those identified by one or more selections may be obtained. For example, data regarding a segment determined to be similar to the selected segment may be acquired.

  In step 2006, the acquired data is stored locally. Data acquired prior to the start of the user's physical activity may be stored in either the device's temporary storage or permanent storage, so that the user can A remote segment matching server is not required to determine matching segments and / or any segments close to the user while performing physical activity.

  In step 2008, location information and performance information related to the user's current activity is compared to the stored data. For example, using at least a portion of the GPS data previously recorded for the user's current activity to match a segment where data is stored locally, including data prefetched from the segment matching server prior to the start of the user activity can do. Alternatively, for example, effort historical performance data determined to match a segment that matches the user's current activity can be used to compare with performance data recorded for the user's current activity so far. In some embodiments, other determinations may be made using location and performance information regarding the user's current activity and locally stored information. For example, using locally stored data, it can be determined whether there is a segment that is close / adjacent to the current location of the user.

  FIG. 21 is a flowchart illustrating one embodiment of a process for setting parameters relating to a filter on data obtained for comparison with performance data of a user's current activity, according to some embodiments. In some embodiments, process 2100 is implemented in system 1500.

  Process 2100 may be utilized to set a parameter that identifies the type of data that the user is interested in (eg, obtained from a segment matching server such as segment matching server 1508 during the user's current activity). Parameters can be used to filter out data that is not of interest to the user. In some embodiments, the selection and definition of process 2100 may be entered by a user, for example, at a user interface associated with the device. In some embodiments, the process 2100 may be a subset of the segments that the user actually wants to match or potentially detect whether they are nearby during the current activity (eg, the user has many segments A subset of performance data related to other users (eg, a user only compares performance with certain other users who are friends) And the user's desired definition of the range of concurrency between at least two users (eg, a user wants to compare his performance data with a “simultaneous” user) Define the scope of simultaneity to include only those users who think that they are close in time or space. Such user performance data is used to identify the desire for) as may be compared as a simultaneous users in the same segment. By setting parameters that can act as a filter as shown in the example, a large amount of data (most of which is potentially undesired for the user using the device) can be focused without retrieving it on the device. It is possible to retrieve data from the segment matching server in an efficient manner that narrows down.

  In step 2102, one or more selections for one or more segments to be matched or detected to be close are retrieved. In some embodiments, the selection for a segment may be an identifier corresponding to the name of the segment (eg, “Old La Honda”) or a characteristic of one or more segments (eg, distance = 30 + miles, The difficulty level = medium and the maximum number of slopes in the segment = 5) may be described. The selection may then be utilized to search for one or more segments corresponding to the description contained within the selection, and the found segment is compared to the recorded GPS data of the user's current activity and the user's It is determined whether the current activity matches or is close to any one or more of the found segments. In other words, using only the corresponding segment of the selection and whether any of them is the segment where the user's current activity is taking place and / or is close to the user's current location Determine.

  In step 2104, one or more selections for one or more other users to be detected are retrieved. In some embodiments, the choice for other users may be that the user potentially compares the performance data of other users in the segment with which the user's current activity is consistent with his performance data in the same segment. It is used to determine what data is what you think. For example, user Barry may want to compare his performance data only with his friend's data. In some embodiments, the selection for other users determines which other users you want to detect when the user is active. For example, a notification that user Barry is doing physical activity in the vicinity of his friend Carrie (Carrie also uses a device such as device 1502) or nearby (eg, the same segment as Barry when Barry is not cycling or a nearby segment) You can set when to receive In some embodiments, the selection for other users to be detected includes an identifier associated with the other user, eg, the user's actual name or nickname associated with the user's account of the segment matching server. In some embodiments, the selection for other users to be detected includes one or more physical characteristics, such as age range, gender, and associated experience level. For example, the user Barry may want to detect a user having physical characteristics similar to that of the user (who may or may not be friends with the user) when he / she is not performing physical activity. Then, since the performance data is compared with such users during Barry's activities, Barry can know the performance contrast with similar individuals.

  At step 2106, a definition of a range of concurrency between at least two users is received. In some embodiments, the definition of a simultaneity range may be a range of time or distance for classifying two or more users within that range as simultaneous. For example, even if two users are cycling along the same segment, they may depart at different times, resulting in each being at a different point in the segment at a given time. However, the user wants to consider another user in the same segment to be concurrent with him, even if the two users have not started the segment at the same time and / or are not cycling side by side There is a case. Thus, for example, a user can define a range of simultaneity up to a distance of 10 miles between two users or a start time difference between two users of up to 2 minutes. In this way, a user can potentially receive feedback data regarding another user who is currently in the same segment but crossed the segment's virtual start line one minute before the user. Thus, when a user receives the knowledge of another concurrent user, the user can be motivated to catch up or overtake that concurrent user.

  FIG. 22 is a flowchart illustrating one embodiment of a process for matching a segment to a user's current activity in accordance with some embodiments. In some embodiments, process 2200 is implemented at device 1502.

  Process 2200 is an example of a technique for determining when the user matches a segment during the user's current activity (ie, when the user is active on the segment).

  In step 2202, location information regarding the user's current activity is recorded. In some embodiments, the location information includes GPS data. In some embodiments, the location information of the user's current activity is recorded at a frequency set by the user or by default settings of a device such as the device 1502 that records the information. In some embodiments, the recorded location information is transmitted to a remote segment matching server, such as remote segment matching server 1508.

  In step 2204, it is determined whether the virtual start line of the segment has been crossed. In some embodiments, at least a portion of the location information recorded so far during the user's current activity is used to cross the virtual start line where the geographical path of the activity is defined for the stored segment. It is determined whether or not. For example, whether or not the virtual start line has been crossed can be determined based on the technique described in FIG. In some embodiments, the determination of step 2204 is made at a segment matching server. In some embodiments, the determination of step 2204 is made at the device if segment data (eg, a set of data defining the segments and their virtual start lines) is stored locally on the device. If it is determined that the virtual start line has been crossed, control proceeds to step 2206. If it is determined that the virtual start line has not yet been crossed, control returns to step 2202, and additional location information regarding the user's current activity is recorded over time.

  In step 2206, it is determined that the segment associated with the crossed start line matches the user's current activity. In some embodiments, for a segment associated with a virtual start line that is determined to have crossed location information of the user's current activity, it is assumed that the user is in that segment. In some embodiments, historical performance data associated with effort determined to match the segment and / or concurrent performance data of current activity of other users determined to match the segment are retrieved from the segment matching server. Or if a copy of such data is available locally on the device, it is retrieved locally. The retrieved data includes, for example, the results of comparing the user's current performance data with the user's historical performance data in the matched segment, as well as the user's current performance data and other user's history in the matched segment and It may be utilized to provide one or more types of feedback data for the user, such as a comparison result with simultaneous performance data.

  In some embodiments, when the stored segment forms a loop and does not have a virtual start line defined for it, in determining whether the user's current activity matches such a loop segment Neither step 2204 nor step 2206 may be performed. Instead, in some embodiments, if location information recorded for the user's current activity crosses at least a portion of the loop segment (which may indicate that the user has entered the loop). It is determined that the current activity matches the loop segment.

  FIG. 23 is a flowchart illustrating one embodiment of a process for determining a user's progress along a segment in accordance with some embodiments. In some embodiments, process 2300 is implemented in system 1500. In some embodiments, process 1800 is performed using process 2300.

  Process 2300 may be utilized after it is determined (in a process such as process 2200) that the user's current activity matches the segment (ie, is being performed on the segment). The process 2300 determines, over time (eg, periodically), whether the user's current activity is continuing on the matched segment, and if so, how long the user is along the segment Can be used to determine if it has advanced. In some embodiments, if it is determined that the user is still traveling on the matched segment, feedback data is provided based at least in part on the determination.

  At step 2302, a segment associated with the user's current activity is determined. In some embodiments, the segment is determined as a segment that matches at least a portion of the location information previously recorded for the user's current activity using a process, such as process 2200.

  In step 2304, it is determined whether the user is still on the segment. In some embodiments, step 2304 is performed at some time after a matched segment is determined. In some embodiments, step 2304 compares the location information recorded so far for the user's current activity with data defining a matched segment (eg, a set of MBRs) to determine if the user's current activity is It is determined whether it is still moving along the segment or has deviated from the segment. For example, if the matched segment is represented as a set of stored MBRs, the location information recorded so far for the user's current activity can also be converted to a set of MBRs. Then, if the MBR associated with the previously recorded location information for the user's current activity almost overlaps at least a portion of the set of MBRs associated with the stored segment, the user's current activity is still a segment Determined to be on top. In some embodiments, the determination of step 2304 is performed at a remote segment matching server, such as segment matching server 1508, or the device when segment data is stored locally on a device, such as device 1502. Is executed. If it is determined that the user is no longer on the segment, process 2300 ends. If it is determined that the user is still on the segment, control proceeds to step 2306.

  At step 2306, the current progress along the segment is determined based at least in part on location information related to the user's current activity so far. For example, it is possible to determine the percentage of a set of MBRs associated with a stored segment that overlaps with the transformed MBR from the previously recorded location information for the user's current activity, and this percentage can be Can be determined as the user's current progress.

  In step 2308, real-time segment performance information related to the user's current activity on the segment based at least in part on the current progress is communicated. In some embodiments, step 2308 is optionally performed. In some embodiments, feedback data of performance information determined based at least in part on the user's determined current progress in the segment is communicated. For example, the set parameters can be used to determine when it is desirable to communicate the current progress to the user. One example is when the user is at an intermediate point in the segment, at which time some performance information (eg, determined based on a comparison of performance data) is communicated to the user. For example, the transmission of such feedback data to the user may be done on the device as an indication and / or audio output, “Old La Honda has passed the midpoint. It has exceeded the record pace of 11 seconds”.

  FIG. 24 is a flowchart illustrating one embodiment of a process for communicating real-time performance information regarding a user's current activity in accordance with some embodiments. In some embodiments, process 2400 is performed in system 1500. In some embodiments, step 1804 of process 1800 is performed using process 2400.

  Process 2400 may be utilized as an example of determining the type of real-time feedback provided to the user during the user's current activity.

  In step 2402, data relating to segments determined to match the user's current activity is retrieved. In some embodiments, it has already been determined that the user's current activity matches the segment (eg, based on location information previously recorded for the user's current activity). In some embodiments, historical performance data associated with an effort determined to match a segment and / or concurrent performance data of other users' current activity determined to match the segment may be remote from a segment matching server 1508, etc. Retrieved from the segment matching server.

  In step 2404, performance data regarding the current activity of the previous user is compared with the retrieved data. In some embodiments, the performance data portion of the relevant data recorded by the device (such as device 1502) for the user's current activity is compared to the retrieved data. Various types of data comparisons can be performed. In some embodiments, the type of comparison to be performed is specified by a set of retrieved configured parameters. For example, performance data regarding a user's current activity in a segment can be compared to the user's own historical performance data in the same segment (eg, derived from the user's previously matched effort). Also, for example, performance data relating to a user's current activity in a segment can be compared to other users 'historical performance data in the same segment (eg, derived from other users' previously matched effort). In another example, performance data regarding a user's current activity in a segment can be compared with performance data of other users in the same segment at the same time.

  At step 2406, results determined based at least in part on the comparison are presented. For example, the comparison results can be provided to the user at the user interface of the device using one or more of images, text, video, and audio.

  Below are some examples of real-time feedback data that can be determined and presented on a device, such as device 1502, when the user is still active or just after the user has completed the activity.

  Examples of feedback data determined based on estimating a user's future performance based on recorded performance data regarding the user's current activity in previous segments include:

“It ’s 34 miles on the 80 Paradise Loop route. At the current pace, we ’ll reach 4:30 pm in 2 hours and 15 minutes.”

“It's about half of the Paradise Loop route. At your full average pace, you will finish in 45 minutes.”

“It's about half of the Paradise Loop route. At the current average pace, we will finish in 35 minutes.”

“About half of the Paradise Loop route. For average riders, the goal is 45 minutes.”

  Examples of feedback data determined based on comparing performance data regarding a user's current activity in a segment with the user's historical performance data in the same segment include:

“Old La Honda has updated his record for 22 seconds”

“Old La Honda has a third-place self-record. It ’s a difference of 13 seconds from the highest one month ago.”

“Currently the middle point of Old La Honda. I ’m 11 seconds faster than my best record.”

“Currently the middle point of Old La Honda. It is 7 seconds below the record pace of my personal record.”

  Examples of feedback data determined based on comparing performance data regarding a user's current activity in a segment with other users' historical or concurrent performance data in the same segment include:

“Old La Honda's best record has been updated. The previous record of Mark Shaw was 22 seconds higher.” In this example, the data related to Mark Shaw is history, not data that is concurrent with the user's current activity at Old La Honda.

“I was 28th in Old La Honda. It was 15 seconds away from 27th place Aaron Foster.” FIG. 25 is a diagram illustrating a screenshot of a user interface displaying a leaderboard for effort completed in the “Marincello Trail” segment, according to some embodiments. The screenshot in this example is related to the smartphone device application. As shown in the screenshot, the various users who completed the segments (Christian Hobbs, Aaron Foster, Mark Shaw, Jane Mitchell, and Rich Adams) are ranked in the ranking table based on their segment completion times. . In this example, the current user Mark Shaw who has just completed the activity in the segment is ranked next to Aaron Foster, which is located in position 27 of the ranking table.

“Current ranking: 1st place Mark S. 2nd place Chris D. 3rd place John D. You are currently in 17th place and the difference from the top is 4:30”. As shown in this example, the user and the user are on the same segment as the user while still performing physical activity (rather than determining the user's standings after the user has completed physical activity) A ranking table can be determined for other concurrent users.

“Currently, Mark Shaw's time is 13 seconds, 300 meters away.” In this example, since Mark Shaw is also active in the same segment as the user's current activity, the data related to Mark Shaw is simultaneous data.

“Currently, Mark Shaw time is 13 seconds below and 300 meters behind.”

“Mark has just finished the Alpine Dam trail. If both continue walking on the Alpine Dam Mt. Tam Loop, they will catch up with the current pace in 30 minutes.”

“There are two riders in front of the Paradise Loop route. Mark S. ahead of 30 seconds, Chris D. ahead of 45 seconds. One rider is behind. Pan T. 5 minutes behind.”

  Of feedback data including nearby segments detected based on comparing location information data related to the user's current activity with stored segment data (eg, segments where the user is not currently there but nearby) Examples include:

“Mark Shaw is 5.0 miles away. He is likely to reach about half of the Paradise Loop route. Today he is already 16 miles ahead.”

“I discovered a new Category 2 trail with a distance of 1.5 miles and an altitude difference of 1500 feet. Would you like to save and name this trail?”

FIG. 26 shows a screenshot of a user interface that displays a list of detected segments (“climbs”) located near the user's current activity, according to some embodiments. The screenshot in this example is related to a smartphone application. As shown in the example, each entry included in the list of nearby segments is listed along with some of the physical characteristics of the segment.

  FIG. 27 is a diagram illustrating a screen shot of a user interface displaying a map of detected segments (“climbs”) located near a user's current activity, according to some embodiments. is there. The screenshot in this example is related to a smartphone application. In the example, the purple pin indicates where each detected segment begins.

  Examples of feedback data including sending notifications to other detected nearby users include:

“Mark Shaw is 1.0 mile away. He has just finished the Alpine Dam trail. If both keep walking on Alpine Dam Mt. Tam Loop, they will catch up in 30 minutes at the current pace. Do you want to send a notification to wait? "

  Examples of feedback data including indications about meeting nearby users include:

“Mark S. and Chris D. are waiting for 10 minutes from the departure point of the Paradise Loop route.”

“Riders from your favorite riding group are about 5 minutes behind in the current segment.”

  Examples of feedback data including sending a challenge to other detected nearby users include:

“Mark S. is 1.0 mile away. Do you send a challenge to win the game at Old La Honda? His personal record is 22 seconds above you. Good luck!”

  Examples of feedback data that include indications of the user's personal performance include:

“We have achieved 100 miles this week. Congratulations!”

“We have achieved 200 miles this month. Congratulations!”

  In some embodiments, parameters set for the user or device may determine which feedback data provided to the user is shared with one or more social networks (eg, Facebook). For example, if the user is currently number 1 in the segment ranking table during the user's physical activity due to parameters set before the user started physical activity, post the article on the user's Facebook wall Can be instructed to do. For example, to communicate with a third-party server (such as a server that supports the Facebook platform), a segment matching server, such as segment matching server 1508, can communicate with the Facebook server using appropriate APIs and authentication information. Once an article is shared on a social network, social network friends or other users may make choices about the article (ie, give users virtual praise). And, for example, the selection may be sent to the user's device to inform the user of the selection of the other user on the social network.

  In some embodiments, the parameters set for a user may determine whether other users can see the real-time progress of the user's current activity, and if so, It may be determined which other users are allowed to view. For example, a website associated with a segment matching server and / or a third party server (such as a server that supports social networks) may be presented with a visual representation of the user's current activity, It can be updated as the user progresses along the matched segment. The visual representation may include markers along the map and / or other data regarding user performance data in the segment. For example, before initiating physical activity, the user can set parameters to indicate that he wants to share his real-time progress along the active matching segment and who can view the progress. For example, a user may give permission to only certain other users (eg, social network user friends) to view their progress in action, or any other user to view their progress You may choose to allow that. In some embodiments, other users who have permission to view the user's real-time progress along the segment can connect the device (eg, portable device or desktop computer) while the user's activity is still ongoing. The progress can be viewed by using to access an appropriate website (eg, a website associated with a segment matching server and / or social network). In some embodiments, the viewing user may also make selections regarding the user's real-time progress (ie, give the user a virtual praise). And, for example, the selection may be sent to the user's device to inform the user of the selection of another user on the website.

Although the embodiments described above have been described in some detail for ease of understanding, the invention is not limited to the details provided. There are many alternative ways of implementing the invention. The disclosed embodiments are illustrative and not intended to be limiting.
Application Example 1: A method for providing real-time segment performance information,
Determining a segment related to the user's current activity based at least in part on at least a portion of the location information recorded so far;
Communicating real-time segment performance information regarding the current activity of the user in the segment;
A method comprising:
Application Example 2: The method of Application Example 1, wherein the determination of the segment associated with the user's current activity includes determining whether the user's current activity matches the segment. Method.
Application example 3: The method according to application example 2, wherein whether or not the current activity of the user matches the segment is determined based on whether at least a part of the position information recorded so far is included in the segment. Determining whether the associated virtual start line is crossed.
Application Example 4: The method according to Application Example 2, wherein whether or not the current activity of the user matches the segment is determined by determining whether at least a part of the position information recorded so far is the segment Determining whether or not the portion associated with is intersected.
Application Example 5: The method according to Application Example 1, wherein the position information includes a Global Positioning System (GPS) point and an associated time stamp at each GPS point.
Application Example 6: The method as described in Application Example 1, further comprising receiving a user configurable selection regarding the transmission of data by the device, receiving one or more trigger event definitions, and a period definition , Receiving one or more definitions relating to battery life saving.
Application Example 7: The method of Application Example 1, wherein the transmission of the real-time segment performance information is based at least in part on feedback data transmitted to the device.
Application Example 8: The method of Application Example 1, wherein the transmission of the real-time segment performance information is based at least in part on feedback data generated at a device.
Application Example 9: The method of Application Example 1, wherein the segment is associated with a user selection of potentially matched segments.
Application Example 10: The method described in Application Example 1, further comprising:
Obtaining data about one or more potentially matched segments in the device,
The acquired segment data is stored locally on the device, and the at least part of the location information and other data relating to the current activity of the user are compared with the data stored locally at the device. The way.
Application Example 11: The method of Application Example 1, wherein the performance information is between the performance data relating to the user's current activity in the segment and stored historical performance data associated with the segment. A method that includes a comparison result.
Application example 12: The method of application example 1, wherein the stored historical performance data includes data relating to one or both of the user and another user.
Application example 13: The method of application example 1, wherein the performance information is stored simultaneously with the performance data relating to the current activity of the user in the segment and the current activity of other users in the segment. A method that includes the results of comparisons with performance data.
Application example 14: The method of application example 1, further receiving a user-configurable selection for one or more other users having performance data compared to the performance data for the user's current activity. A method comprising:
Application Example 15: The method described in Application Example 1, further receiving a user configurable selection regarding the range of simultaneity,
A method wherein performance data of user activities within the range are compared to each other.
Application Example 16: The method according to Application Example 1, further comprising transmitting at least part of the performance information to a social network operated by a third party.
Application Example 17: The method of Application Example 1, further comprising receiving a response from a social network operated by the third party based at least in part on the transmitted portion of the performance information. A method of providing.
Application Example 18: The method of Application Example 1, further comprising determining current progress regarding the current activity of the user in the segment.
Application example 19: The method of application example 1, further comprising determining whether another segment exists near the current location of the user's current activity.
Application Example 20: A system for providing real-time segment performance information,
A processor,
Determining a segment related to the user's current activity based at least in part on at least a portion of the location information recorded so far;
A processor configured to communicate real-time segment performance information regarding the current activity of the user in the segment;
A memory connected to the processor and configured to provide instructions to the processor;
A system comprising:
Application example 21: The system of application example 20, wherein the determination of the segment associated with the current activity of the user includes determining whether the current activity of the user matches the segment. system.
Application example 22: The system according to application example 20, wherein the processor further receives a user-configurable selection for transmission of data by the device and receives one or more trigger event definitions. Configured to receive a user-configurable selection for sending data by the device, including one or more of: receiving a period definition, receiving one or more definitions related to battery life saving. The system.
Application example 23: The system according to application example 20, wherein the transmission of the real-time segment performance information is based at least in part on feedback data transmitted to the device.
Application example 24: The system of application example 20, wherein the transmission of the real-time segment performance information is based at least in part on feedback data generated at the device.
Application Example 25: The system according to Application Example 20, wherein the processor further includes:
Configured to obtain data about one or more potentially matched segments to the device;
The acquired segment data is stored locally on the device, and the at least part of the location information and other data relating to the current activity of the user are compared with the data stored locally at the device. System.
Application example 26: The system of application example 20, wherein the performance information is between the performance data relating to the current activity of the user in the segment and stored historical performance data associated with the segment. System including comparison results.
Application example 27: The system according to application example 20, wherein the performance information is stored simultaneously with the performance data relating to the current activity of the user in the segment and the current activity of other users in the segment. A system that includes the results of comparisons with performance data.
Application example 28: The system of application example 20, wherein the processor is further user configurable for one or more other users having performance data compared to the performance data for the user's current activity. A system that is configured to receive a selection.
Application Example 29: The system of application example 20, wherein the processor is further configured to receive a user-configurable selection for a range of concurrency;
A system in which performance data of user activity within the range is compared to each other.
Application Example 30: A computer program product for providing real-time segment performance information, wherein the computer program product is embodied in a persistent computer-readable storage medium,
Computer instructions for determining a segment associated with the user's current activity based at least in part on at least a portion of the location information recorded so far;
Computer instructions for communicating real-time segment performance information regarding the user's current activity on the segment;
A computer program product comprising:

Claims (24)

A method for providing real-time segment performance information,
Receiving a definition of a range of simultaneity indicating a range in which at least two users engaged in physical activity are concurrent with each other;
Determining a segment matching the current activity of the first user based at least in part on at least a portion of the recorded location information of the first user , the first user's recorded Determining a segment that matches the current activity of the first user, including determining that at least a portion of the location information matches at least a portion of the set of geographic information associated with the segment. ,
Determining the segment that matches the current activity of the second user based at least in part on at least a portion of the recorded location information of the second user;
Determining whether the second user is a concurrent user for the first user based at least on the definition of the range of concurrency;
Deliver real-time segment performance information regarding current activities of the first user in the segment based at least in part on the determination of whether the second user is a concurrent user of the first user about,
A method comprising: The method of claim 1 , wherein the determination that the current activity of the first user matches the segment is that at least a portion of the recorded location information of the first user is in the segment. Determining that the associated virtual start line is crossed. The method of claim 1 , wherein the determination that the current activity of the first user matches the segment is that at least a portion of the recorded location information of the first user is in the segment. Determining that the associated portions are crossed.   The method of claim 1, wherein the location information includes a Global Positioning System (GPS) point and an associated time stamp at each GPS point.   The method of claim 1, wherein the transmission of real-time segment performance information is based at least in part on feedback data transmitted to a device.   The method of claim 1, wherein the transmission of real-time segment performance information is based at least in part on feedback data generated at a device.   The method of claim 1, wherein the segment is associated with a user selection of potentially matched segments. The method of claim 1, further comprising:
Obtaining data about one or more potentially matched segments in the device,
The obtained segment data is stored locally on the device, the at least part of the recorded location information of the first user, and other data relating to the current activity of the first user are stored in the device And compared with the locally stored data. The method according to claim 1, wherein the performance information includes Rupa performance data relates to a current activity of the first user in the segment, with the stored historical performance data associated with said segment A method that includes comparison results between. The method of claim 1, wherein the stored historical performance data includes data relating to one or both of the first user and another user. The method according to claim 1, wherein the performance information includes Rupa performance data relates to a current activity of the first user in the segment, is stored for the current activities of other users in the segment A method that includes results of comparisons with concurrent performance data. The method of claim 1, further comprising receiving a user configurable selection for one or more other users having performance data compared to the performance data for the first user's current activity. A method comprising:   The method of claim 1, further comprising transmitting at least a portion of the performance information to a social network operated by a third party.   The method of claim 1, further comprising receiving a response from a social network operated by the third party based at least in part on the transmitted portion of the performance information. The method of claim 1, further comprising : current progress regarding current activity of the first user in the segment based at least in part on the recorded performance information of the first user. A method comprising determining. The method of claim 1, further comprising determining whether another segment exists near a current location of the first user's current activity. A system for providing real-time segment performance information,
A processor,
Receive a definition of a range of simultaneity indicating a range in which at least two users engaged in physical activity are concurrent with each other;
Determining a segment matching the current activity of the first user based at least in part on at least a portion of the recorded location information of the first user, and matching the current activity of the first user Determining at least a portion of the recorded location information of the first user matches at least a portion of a set of geographic information associated with the segment;
Determining the segments that match the second user's current activity based at least in part on at least a portion of the second user's recorded location information;
Determining whether the second user is a concurrent user for the first user based at least on the definition of the scope of concurrency;
Deliver real-time segment performance information regarding current activities of the first user in the segment based at least in part on the determination of whether the second user is a concurrent user of the first user A processor configured to:
A memory connected to the processor and configured to provide instructions to the processor;
A system comprising: The system of claim 17 , wherein the transmission of the real-time segment performance information is based at least in part on feedback data sent to a device. 18. The system of claim 17 , wherein the transmission of real-time segment performance information is based at least in part on feedback data generated at a device. The system of claim 17 , wherein the processor further comprises:
Configured to obtain data about one or more potentially matched segments to the device;
The obtained segment data is stored locally on the device, the at least part of the recorded location information of the first user, and other data relating to the current activity of the first user are: A system that is compared to the locally stored data at a device. The system of claim 17, wherein the performance information includes Rupa performance data relates to a current activity of the first user in the segment, with the stored historical performance data associated with said segment The system, including the comparison results between. The system of claim 17, wherein the performance information includes Rupa performance data relates to a current activity of the first user in the segment, is stored for the current activities of other users in the segment A system that includes results of comparisons with concurrent performance data. The system of claim 17, wherein the processor is further user settings for one or more other users having performance data to be compared with the first Rupa performance data relates to a current user activity A system that is configured to receive possible selections. A computer program for providing a real-time segment performance information,
A function for receiving a definition of a range of simultaneity indicating a range in which at least two users performing physical activity are concurrent with each other;
A function for determining a segment that matches a current activity of the first user based at least in part on at least a portion of the recorded location information of the first user , the first user's Determining a segment that matches the current activity of the first user, including determining that at least a portion of the recorded location information matches at least a portion of a set of geographic information associated with the segment; With the function to
A function for determining the segment that matches a current activity of the second user based at least in part on at least a portion of the recorded location information of the second user;
A function for determining whether the second user is a concurrent user for the first user based at least on the definition of the range of simultaneity;
Deliver real-time segment performance information regarding current activities of the first user in the segment based at least in part on the determination of whether the second user is a concurrent user of the first user to realize a function for a computer, the computer program.

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